--- title: "From Monolith to Plugins: An AI-Assisted Architectural Refactor" permalink: /futureproof/ai-assisted-monolith-to-plugin-refactor/ description: "I'm at a crossroads with my tool system, torn between the flow state of a single massive file and the practical need for modularity, especially for AI collaboration. Today, I'm committing to the plugin model for my MCP tools. The immediate task is to perform the delicate surgery of moving the monolithic `mcp_tools.py` into its new home inside the `tools/` directory. This involves a lot of careful command-line search-and-replace, followed by creating a true, automatic discovery system so the architecture is not just moved, but genuinely improved." meta_description: A step-by-step case study of refactoring a monolithic Python file into a plugin system using rg, sed, git, and an AI assistant for strategic planning. meta_keywords: Python refactoring, monolith to microservices, plugin architecture, command-line tools, rg, sed, git, AI-assisted development, Gemini CLI, mcp_tools.py, software architecture layout: post sort_order: 3 --- ## Setting the Stage: Context for the Curious Book Reader This entry captures a critical phase in the architectural evolution of **Pipulate**, a software project designed for deep, ongoing collaboration with local AI agents. The author grapples with a common developer dilemma: the trade-off between large, self-contained code files that enhance personal workflow (`WET` code, or "Write Everything Twice") and modular, "plugin-style" systems that are often considered best practice. This specific session focuses on refactoring the system's **MCP (Machine Communication Protocol) tools**—the individual commands that AI agents use to interact with the application and the outside world. The narrative follows the author's decision-making process, moving from a single massive file (`mcp_tools.py`) towards a more organized directory of tools. This isn't just a simple code cleanup; it's a strategic move to improve the author's ability to work with AI coding assistants, which struggle with the context of very large files. The entry provides a transparent, real-time look at the planning, execution, and verification of a significant code refactoring, showcasing a blend of command-line mastery, AI collaboration, and a unique software development philosophy. --- ## Embracing Modularity: The Decision to Refactor Okay so what are we doing? We're creating a sort of butterfly net for the AI boom for the small guy who has some interest in incubating a genie in a bottle like a Tamagotchi digital pet, but also like a hermit crab moving from hardware shell to hardware shell as Moore's Law pushes the power of that hardware shell forward. Today it's our home Macbooks and gaming rig with an NVidia RTX GPU or even a Jetson Nano. Tomorrow, who knows? But it will still be able to run the code you write today because otherwise NVidia wouldn't be on its stellar rise. Things will change. Things always change. You'll have to keep learning and adapting, but underlying it all is a kind of technical skills Kung Fu that doesn't change. You need exactly those skills to keep interacting well with your Tamagotchi genie hermit crab — which I happen to name mine Chip O'Theseus but you can name yours whatever you like — and the skills to migrate it forward smoothly from hardware shell to hardware shell over the years. So yes, churn. But also no, not so much churn that you can't capture some wind in your sails based on a certain set of skills that are never rendered obsolete. The work can't be done at a single pass but with each pass I want to increase the odds that the remaining work can be done at a single pass. This is done through the increasing ability to delegate work to an intelligent assistant with you working more like a boss. But just as a boss really has to understand things down to a low level and in a pinch be able to do the laborious work themselves, so must you. A good boss doesn't work at such high abstractions that they lose track of the details where all the difference may be made. So sometimes a pass is just to make the next pass easier. But it's not always by making more and more abstractions to make the work easier. Sometimes it's really just getting in there to understand the details better. Instead of more code it might be just the right documentation embedded into the code to instill recurring "ah-ha!" moments of insight that have to perpetually be compelled to happen again because that magical context is fades rapidly away. This next round of work builds upon a few things I've done recently and now that I've gathered the critical insights from AI unobtrusively examining my code, I'm going to do the coding work myself. It is a badge of honor that my files are too big for AI to easily edit. I'm better in vim at editing big files than they are with their tool calling. It's a double whammy really because the big files are difficult for their context windows and for their editing tools. Yet the big files are a source of advantage for me because it's easier to jump around inside a single file than it is to navigate across multiple files while staying in flow state. That's a vim navigation thing. It's possible across multiple files but finding which file to be in and navigating across them is a point of friction (with or without vim). This thinking almost convinced me to undo a plugin system for MCP tools I recently made mostly to pander to AI to get a massive monolithic mcp_tool.py file down to where they could more easily help me but ultimately I'm going with the broken out file model for MCP tools. I already did that for workflows and CRUD apps having gone through a very similar through process and almost capitulation to more modern modular methodology. That's not to say that I've given up my singular monolithic files. It's just that different concerns won out in the question of whether to modularize modules. What makes a module? Workflows. CRUD apps. And now MCP tools. Little else. Okay, things need to get done. And the outer framework that you create puts rails of a sort on the range of things you can easily do. It's like a Roger Penrose light-cone of probability. The world of possible outcomes is called the phase space. Phase spaces can be larger or smaller based on how rigid those rails, or the physical laws of the universe you're creating are. Right now the Pipulate phase space is pretty small because it focus on the creation of linear sequential workflows. But you can chat with an AI as you step through those workflows and the AI can make any sort of tool-call you want in those chats, and those tool-calls can be wired into the workflows themselves. And any step in a workflow could actually be a non-linear or agentic process. So it's really only the "outer shape" of a workflow as a 1, 2, 3 step procedure that's strongly compelled. These individual tool-calls that I'm working on now are more like individual Unix-like commands that are for particular specialized purposes, but which can be used in combination to great effect. And so the shape of the light-cones of possibilities and size of the phase space increases because these tools exist and are at your disposal. But overall everything is made to look simple, like a Jupyter Notebook where you just click Next, Next, Next. It's an envelope of simplicity wrapping very powerful box of tools that you only optionally tap, and often it's the AI thinking to tap these tools on your behalf, so again it's less cognitive load on you the human. Okay, that's enough warm up. ## Surveying the Blast Radius with `rg` > I know it's a lot to look at. The gist is that this is a `grep` which is a > global search for the occurrence of references to a file that I'm going to be > moving. This gives me a general sense of the work ahead of me based on the > number or references to it. ```bash [mike@nixos:~/repos/pipulate]$ vim .gitignore [mike@nixos:~/repos/pipulate]$ rg mcp_tools README.md 693:- Review `mcp_tools.py` for MCP protocol capabilities 1087: ├── mcp_tools.py # MCP protocol tools - the AI assistant interface 1385:mcp_tools.py # AI assistant interface pyproject.toml 46:py-modules = ["cli", "server", "common", "config", "ai_dictdb", "mcp_tools", "__init__"] tools/__init__.py 9: from .botify_mcp_tools import ( 19: # If botify_mcp_tools isn't available, that's okay 23: from .advanced_automation_mcp_tools import ( 33: # If advanced_automation_mcp_tools isn't available, that's okay 40: from .botify_mcp_tools import CORE_BOTIFY_TOOLS tools/README.md 9:Instead of breaking down the entire monolithic `mcp_tools.py` into many small files (which created complexity explosion), we use **targeted extraction** of specific domains when needed. 16:├── botify_mcp_tools.py # Botify-specific MCP tools (8 tools) 24:| Original `mcp_tools.py` | 357,124 chars | ~89,281 tokens | - | 25:| `tools/botify_mcp_tools.py` | 17,610 chars | ~4,402 tokens | **95.1%** | 31:from tools.botify_mcp_tools import botify_ping, botify_get_full_schema 41:from tools.botify_mcp_tools import * 47:- **OLD**: Include full `mcp_tools.py` (89,281 tokens) 48:- **NEW**: Include only `tools/botify_mcp_tools.py` (4,402 tokens) 75:- `browser_mcp_tools.py` - Browser automation tools 76:- `analysis_mcp_tools.py` - Analysis and reporting tools 77:- `ui_mcp_tools.py` - UI interaction tools tools/advanced_automation_mcp_tools.py 2:Advanced Automation & AI MCP Tools - Extracted from mcp_tools.py for token optimization 5:and AI training tools extracted from the monolithic mcp_tools.py. 7:Line range: 4830-7818 from original mcp_tools.py 35: from mcp_tools import ( 47: return {"success": False, "error": "mcp_tools not available"} 387: from mcp_tools import browser_hijack_workflow_complete 1863: "level": "2_mcp_tools", 1870: "level": "2_mcp_tools", 3021: 'mcp_tools_access': 'Four MCP tools for programmatic conversation management' tools/botify_mcp_tools.py 2:Botify MCP Tools - Extracted from mcp_tools.py for focused token optimization discover_mcp_tools.py 28: print(" 💡 Try: .venv/bin/python discover_mcp_tools.py") 31:def discover_mcp_tools(): 32: """Discover all MCP tools available in mcp_tools.py""" 34: # Import the mcp_tools module 36: import mcp_tools 38: print(f"❌ Error importing mcp_tools: {e}") 40: print(f" .venv/bin/python discover_mcp_tools.py") 50: mcp_tools = [] 51: for name, obj in inspect.getmembers(sys.modules['mcp_tools']): 56: mcp_tools.append(name) 69: for tool in sorted(mcp_tools): 105: for tool in mcp_tools: 107: func = getattr(sys.modules['mcp_tools'], tool) 129: from mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 132: register_all_mcp_tools() 153:.venv/bin/python discover_mcp_tools.py 156:.venv/bin/python -c "import asyncio; from mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" 159:.venv/bin/python -c "import asyncio; from mcp_tools import ai_capability_test_suite; result = asyncio.run(ai_capability_test_suite({'test_type': 'quick'})); print('Success Rate:', result.get('success_rate', 'N/A'), '%')" 162:.venv/bin/python -c "import asyncio; from mcp_tools import ai_self_discovery_assistant; result = asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'})); print('Tools found:', result.get('total_tools_available', 'N/A'))" 165:.venv/bin/python -c "import asyncio; from mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" 176: results = discover_mcp_tools() 187: print(f"💡 Fix: Use .venv/bin/python discover_mcp_tools.py") cli.py 60:def discover_mcp_tools(show_all=False, tool_name=None): 82: from mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 83: register_all_mcp_tools() 109: from discover_mcp_tools import discover_mcp_tools as run_discovery 147: console.print("❌ [bold red]Error:[/bold red] discover_mcp_tools.py not found in current directory") 160: from mcp_tools import register_all_mcp_tools 161: register_all_mcp_tools() 163: # Import the server's registry - with inline architecture, we need to get it from mcp_tools 164: from mcp_tools import MCP_TOOL_REGISTRY 407: discover_mcp_tools(show_all=args.all, tool_name=args.tool) assets/pipulate-init.js 1909:- mcp_tools.py (MCP tool definitions) mcp_tools.py 862:def register_all_mcp_tools(): 1633:from mcp_tools import execute_complete_session_hijacking 3896:# All tools are now registered in register_all_mcp_tools() function above 3927: from mcp_tools import register_all_mcp_tools 3928: register_all_mcp_tools() 3941: # Try to discover tools using the same method as discover_mcp_tools.py 3946: mcp_module = sys.modules.get('mcp_tools') 4080: "solution": "Check server startup logs, ensure tool is registered in register_all_mcp_tools()", 4292: mcp_result = await test_mcp_tools_availability() 4293: test_results["results"]["mcp_tools"] = mcp_result 4356:async def test_mcp_tools_availability() -> dict: 4361: from mcp_tools import builtin_get_cat_fact 4368: "mcp_tools_accessible": True, 4382: "mcp_tools_accessible": True, 4389: if os.path.exists("mcp_tools.py") and os.path.exists("server.py"): 4392: "mcp_tools_accessible": True, 4607: return await test_mcp_tools_availability() 4646: test_file = "mcp_tools.py" server.py 71:import mcp_tools 85:from mcp_tools import register_all_mcp_tools 88:# Initialize MCP_TOOL_REGISTRY before importing mcp_tools to avoid circular dependency issues 102:# Pass our registry to mcp_tools so they use the same instance 103:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 174:# 🔧 FINDER_TOKEN: rotate_looking_at_directory moved to mcp_tools.py to eliminate circular imports 401:# Initialize MCP_TOOL_REGISTRY before importing mcp_tools to avoid circular dependency issues 404:# Pass our registry to mcp_tools so they use the same instance 405:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 724:# 🔧 FINDER_TOKEN: register_mcp_tool moved to mcp_tools.py (superior error handling) 725:# Use register_mcp_tool from mcp_tools.py - it has better error handling for uninitialized registry 727:# MCP tools are now consolidated in mcp_tools.py - see register_all_mcp_tools() 731:# Tools now registered via register_all_mcp_tools() from mcp_tools.py 736:# _pipeline_state_inspector, etc.) have been moved to mcp_tools.py for better organization. 737:# See register_all_mcp_tools() in mcp_tools.py for complete tool registration. 739:# 🔧 FINDER_TOKEN: _read_botify_api_token moved to mcp_tools.py to eliminate duplication 742:# All Botify MCP tools moved to mcp_tools.py for better maintainability: 749:# ALL Botify tools are now registered via register_all_mcp_tools() in mcp_tools.py: 756:# are now registered via register_all_mcp_tools() in mcp_tools.py 758:# are in mcp_tools.py. The simple duplicate versions have been removed from server.py. 762:# are now registered via register_all_mcp_tools() in mcp_tools.py 4402:# Ensure mcp_tools has the correct registry reference 4403:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 4404:register_all_mcp_tools() 4438: mcp_tools_count=tool_count, 7161: "available_mcp_tools": { plugins/130_gap_analysis.py 493: from mcp_tools import browser_scrape_page, browser_analyze_scraped_page modules/ascii_displays.py 565: mcp_tools_count: int, 590: status_table.add_row("🔧 MCP Tools", "✅ Ready", f"{mcp_tools_count} tools available") 602: commands_table.add_row("🎭 Session Hijack", ".venv/bin/python -c \"import asyncio; from mcp_tools import execute_complete_session_hijacking; asyncio.run(execute_complete_session_hijacking({}))\"") 603: commands_table.add_row("🧠 AI Discovery", ".venv/bin/python -c \"from mcp_tools import ai_self_discovery_assistant; import asyncio; asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'}))\"") 634:✅ MCP Tools: {mcp_tools_count} tools available modules/ai_tool_discovery_simple_parser.py 38:from mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 176: register_all_mcp_tools() browser_automation/automation_recipes/README_SAVE_LOAD_AUTOMATION.md 202:from mcp_tools import browser_save_all_data_single_session 209:from mcp_tools import browser_load_all_data_single_session modules/server_logging.py 147: # 🔧 FINDER_TOKEN: MAX_ROLLED_LOOKING_AT_DIRS moved to mcp_tools.py (used by rotate_looking_at_directory) helpers/prompt_foo/generate_files_list.py 277: FileEntry("mcp_tools.py", False, "MCP tools - AI assistant interface"), 285: FileEntry("discover_mcp_tools.py", True, "MCP tool discovery and validation"), helpers/prompt_foo/prompt_foo.py 12:# extracted MCP tools (botify_mcp_tools.py, advanced_automation_mcp_tools.py) [mike@nixos:~/repos/pipulate]$ ``` And that's all my references to `mcp_tools.py` that I have to keep in mind when I move it into `tools/`. I had to edit the `cruft` folder into `.gitingore` (for now) to make this reasonably sized. Hmmm. Searching and replacing on just `mcp_tools` is not going to be easy because of naming collisions. First I'm going to remove any reference to mcp_tools from my prompt_foo system. Next I want to eliminate those naming collisions which are mostly on: ```bash [mike@nixos:~/repos/pipulate/tools]$ ls -la total 184 drwxr-xr-x 3 mike users 4096 Sep 9 19:30 . drwxr-xr-x 22 mike users 4096 Sep 13 14:18 .. -rw-r--r-- 1 mike users 144122 Sep 9 17:59 advanced_automation_mcp_tools.py -rw-r--r-- 1 mike users 17661 Sep 9 19:30 botify_mcp_tools.py -rw-r--r-- 1 mike users 1540 Sep 8 05:31 __init__.py drwxr-xr-x 2 mike users 4096 Sep 9 19:32 __pycache__ -rw-r--r-- 1 mike users 2908 Sep 8 05:31 README.md [mike@nixos:~/repos/pipulate/tools]$ ``` --- ## The Cleanup Crew: Renaming Modules with `sed` and `git` > This is the work before the work. A lot of things have the words `mcp_tools` > in them, like larger files with that as part of the name. This is practice > using my recent `rg | xargs sed` skills to just do some file renaming without > breaking references. So first I test my newly developing command-line search and replace abilities: ```bash [mike@nixos:~/repos/pipulate/tools]$ \rg -l --null botify_mcp_tools | xargs -0 sed -i 's/botify_mcp_tools/botify_tools/g' [mike@nixos:~/repos/pipulate/tools]$ git mv botify_mcp_tools.py botify_tools.py [mike@nixos:~/repos/pipulate/tools]$ ``` I do the same for `botify_mcp_tools.py` but manually in vim because there were so many fewer occurrences. I'm also going to do `discover_mcp_tools.py`: ```bash [mike@nixos:~/repos/pipulate]$ rg discover_mcp_tools.py discover_mcp_tools.py 28: print(" 💡 Try: .venv/bin/python discover_mcp_tools.py") 40: print(f" .venv/bin/python discover_mcp_tools.py") 153:.venv/bin/python discover_mcp_tools.py 187: print(f"💡 Fix: Use .venv/bin/python discover_mcp_tools.py") mcp_tools.py 3941: # Try to discover tools using the same method as discover_mcp_tools.py cli.py 147: console.print("❌ [bold red]Error:[/bold red] discover_mcp_tools.py not found in current directory") [mike@nixos:~/repos/pipulate]$ rg discover_mcp_tools.py -l --null cli.pydiscover_mcp_tools.pymcp_tools.py [mike@nixos:~/repos/pipulate]$ \rg discover_mcp_tools.py -l --null | xargs -0 sed 's/discover_mcp_tools/discover_tools/g' -i [mike@nixos:~/repos/pipulate]$ git mv discover_mcp_tools.py discover_tools.py [mike@nixos:~/repos/pipulate]$ git status On branch normalize Your branch is up to date with 'origin/normalize'. Changes to be committed: (use "git restore --staged ..." to unstage) renamed: discover_mcp_tools.py -> discover_tools.py Changes not staged for commit: (use "git add ..." to update what will be committed) (use "git restore ..." to discard changes in working directory) modified: .gitignore modified: cli.py modified: discover_tools.py modified: mcp_tools.py [mike@nixos:~/repos/pipulate]$ ``` Alright, that's a nice general cleanup. One interesting thing I did was toss the `cruft` folder into the `.gitignore` to reduce the noise in the global repo searching. `rg` abides by the `.gitignore` and this is a great shortcut, but I do have one question to clarify. If files in a folder are already in a git repo and then you add that folder to the `.gitignore` do those files stay in the repo? files in a folder are already in a git repo and then you add that folder to the `.gitignore` do those files stay in the repo? **Gemini**: Yes, if files in a folder are already being tracked by Git, and you then add that folder to your `.gitignore` file, the files will **remain in the repository**. The `.gitignore` file only prevents untracked files from being added to the repository. It does not affect files that are already being tracked. Git will continue to monitor and include changes to those files in subsequent commits, even though their parent folder is now listed in `.gitignore`. ### How to Untrack Previously Committed Files If you want to stop tracking files that have already been committed and are now listed in your `.gitignore`, you need to explicitly remove them from the Git index. This can be done without deleting the files from your local working directory by using the following command: ```bash git rm --cached ``` For an entire folder, you would use the recursive option: ```bash git rm -r --cached ``` After running this command, the files will no longer be tracked by Git, but they will still exist in your local folder. The next time you commit, this removal from tracking will be recorded in the repository's history. This action will also lead to the deletion of these files from the working directories of other contributors when they pull the changes. --- **Me**: Okay, that's a good answer. That means I can leave the cruft folder in .gitignore for good long stretches and it's only when I move new stuff into the cruft folder that I want to take it out of .gitignore to do a commit so I don't lose that file. This has now gotten the surveying prior to the careful surgical search and replace updating mcp_tool references down to: ```bash [mike@nixos:~/repos/pipulate]$ rg mcp_tools cli.py 82: from mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 83: register_all_mcp_tools() 160: from mcp_tools import register_all_mcp_tools 161: register_all_mcp_tools() 163: # Import the server's registry - with inline architecture, we need to get it from mcp_tools 164: from mcp_tools import MCP_TOOL_REGISTRY pyproject.toml 46:py-modules = ["cli", "server", "common", "config", "ai_dictdb", "mcp_tools", "__init__"] tools/botify_tools.py 2:Botify MCP Tools - Extracted from mcp_tools.py for focused token optimization mcp_tools.py 862:def register_all_mcp_tools(): 1633:from mcp_tools import execute_complete_session_hijacking 3896:# All tools are now registered in register_all_mcp_tools() function above 3927: from mcp_tools import register_all_mcp_tools 3928: register_all_mcp_tools() 3946: mcp_module = sys.modules.get('mcp_tools') 4080: "solution": "Check server startup logs, ensure tool is registered in register_all_mcp_tools()", 4292: mcp_result = await test_mcp_tools_availability() 4293: test_results["results"]["mcp_tools"] = mcp_result 4356:async def test_mcp_tools_availability() -> dict: 4361: from mcp_tools import builtin_get_cat_fact 4368: "mcp_tools_accessible": True, 4382: "mcp_tools_accessible": True, 4389: if os.path.exists("mcp_tools.py") and os.path.exists("server.py"): 4392: "mcp_tools_accessible": True, 4607: return await test_mcp_tools_availability() 4646: test_file = "mcp_tools.py" tools/advanced_automation_tools.py 2:Advanced Automation & AI MCP Tools - Extracted from mcp_tools.py for token optimization 5:and AI training tools extracted from the monolithic mcp_tools.py. 7:Line range: 4830-7818 from original mcp_tools.py 35: from mcp_tools import ( 47: return {"success": False, "error": "mcp_tools not available"} 387: from mcp_tools import browser_hijack_workflow_complete 1863: "level": "2_mcp_tools", 1870: "level": "2_mcp_tools", 3021: 'mcp_tools_access': 'Four MCP tools for programmatic conversation management' discover_tools.py 32: """Discover all MCP tools available in mcp_tools.py""" 34: # Import the mcp_tools module 36: import mcp_tools 38: print(f"❌ Error importing mcp_tools: {e}") 50: mcp_tools = [] 51: for name, obj in inspect.getmembers(sys.modules['mcp_tools']): 56: mcp_tools.append(name) 69: for tool in sorted(mcp_tools): 105: for tool in mcp_tools: 107: func = getattr(sys.modules['mcp_tools'], tool) 129: from mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 132: register_all_mcp_tools() 156:.venv/bin/python -c "import asyncio; from mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" 159:.venv/bin/python -c "import asyncio; from mcp_tools import ai_capability_test_suite; result = asyncio.run(ai_capability_test_suite({'test_type': 'quick'})); print('Success Rate:', result.get('success_rate', 'N/A'), '%')" 162:.venv/bin/python -c "import asyncio; from mcp_tools import ai_self_discovery_assistant; result = asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'})); print('Tools found:', result.get('total_tools_available', 'N/A'))" 165:.venv/bin/python -c "import asyncio; from mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" plugins/130_gap_analysis.py 493: from mcp_tools import browser_scrape_page, browser_analyze_scraped_page README.md 693:- Review `mcp_tools.py` for MCP protocol capabilities 1087: ├── mcp_tools.py # MCP protocol tools - the AI assistant interface 1385:mcp_tools.py # AI assistant interface assets/pipulate-init.js 1909:- mcp_tools.py (MCP tool definitions) modules/ai_tool_discovery_simple_parser.py 38:from mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 176: register_all_mcp_tools() modules/ascii_displays.py 565: mcp_tools_count: int, 590: status_table.add_row("🔧 MCP Tools", "✅ Ready", f"{mcp_tools_count} tools available") 602: commands_table.add_row("🎭 Session Hijack", ".venv/bin/python -c \"import asyncio; from mcp_tools import execute_complete_session_hijacking; asyncio.run(execute_complete_session_hijacking({}))\"") 603: commands_table.add_row("🧠 AI Discovery", ".venv/bin/python -c \"from mcp_tools import ai_self_discovery_assistant; import asyncio; asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'}))\"") 634:✅ MCP Tools: {mcp_tools_count} tools available modules/server_logging.py 147: # 🔧 FINDER_TOKEN: MAX_ROLLED_LOOKING_AT_DIRS moved to mcp_tools.py (used by rotate_looking_at_directory) browser_automation/automation_recipes/README_SAVE_LOAD_AUTOMATION.md 202:from mcp_tools import browser_save_all_data_single_session 209:from mcp_tools import browser_load_all_data_single_session server.py 71:import mcp_tools 85:from mcp_tools import register_all_mcp_tools 88:# Initialize MCP_TOOL_REGISTRY before importing mcp_tools to avoid circular dependency issues 102:# Pass our registry to mcp_tools so they use the same instance 103:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 174:# 🔧 FINDER_TOKEN: rotate_looking_at_directory moved to mcp_tools.py to eliminate circular imports 401:# Initialize MCP_TOOL_REGISTRY before importing mcp_tools to avoid circular dependency issues 404:# Pass our registry to mcp_tools so they use the same instance 405:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 724:# 🔧 FINDER_TOKEN: register_mcp_tool moved to mcp_tools.py (superior error handling) 725:# Use register_mcp_tool from mcp_tools.py - it has better error handling for uninitialized registry 727:# MCP tools are now consolidated in mcp_tools.py - see register_all_mcp_tools() 731:# Tools now registered via register_all_mcp_tools() from mcp_tools.py 736:# _pipeline_state_inspector, etc.) have been moved to mcp_tools.py for better organization. 737:# See register_all_mcp_tools() in mcp_tools.py for complete tool registration. 739:# 🔧 FINDER_TOKEN: _read_botify_api_token moved to mcp_tools.py to eliminate duplication 742:# All Botify MCP tools moved to mcp_tools.py for better maintainability: 749:# ALL Botify tools are now registered via register_all_mcp_tools() in mcp_tools.py: 756:# are now registered via register_all_mcp_tools() in mcp_tools.py 758:# are in mcp_tools.py. The simple duplicate versions have been removed from server.py. 762:# are now registered via register_all_mcp_tools() in mcp_tools.py 4402:# Ensure mcp_tools has the correct registry reference 4403:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 4404:register_all_mcp_tools() 4438: mcp_tools_count=tool_count, 7161: "available_mcp_tools": { [mike@nixos:~/repos/pipulate]$ ``` --- ## AI as a Surgical Assistant: A Four-Step Refactoring Plan > Yikes! That was all just the prep work for the surgery, not the main act. I > got rid of interfering clutter. There have been no global search and replaces > yet. I know how to do them manually now, but still I want the AI to guide me. > This is major surgery and I'm no surgeon. **Me**: Okay Gemini CLI. Help me think through the next steps. Moving mcp_tools.py into the tools folder is going to break things all over the place, but I should be able to fix it with a global search and replace similar to the ones you've seen be carry out. Help me plan my next moves. **Gemini CLI**: You've done an excellent job of preparing the battlefield. The preliminary cleanup and the rg analysis give us a perfect map of what needs to be done. Moving a central file like mcp_tools.py is a delicate operation, but with this preparation, it's entirely manageable. Here is a strategic plan for your next moves, designed to be as clean and safe as possible. The Plan: A Four-Step Surgical Strike The goal is to perform the move and then surgically update all references in a single, logical pass. --- Step 1: The Move (The Point of No Return) This is the first and most straightforward action. It officially places the monolith inside the new plugin structure. git mv mcp_tools.py tools/ After this, git status will show one renamed file, and everything will be broken. This is expected. --- Step 2: The Great Update (Global Search & Replace) This is the core of the operation. You'll perform a global search and replace across the project. Based on your rg output, here are the key transformations you need to make: 1. Standard Imports: This will be the most common change. * Find: import mcp_tools * Replace with: import tools.mcp_tools as mcp_tools * Why `as mcp_tools`? This alias is crucial. It means any subsequent code in that file that refers to mcp_tools.some_function() will continue to work without any further changes. It's the safest and most efficient replacement. 2. "From" Imports: * Find: from mcp_tools import * Replace with: from tools.mcp_tools import 3. String Literals and Dynamic Imports: These are subtle but critical. * Find: 'mcp_tools' (specifically in sys.modules.get('mcp_tools')) * Replace with: 'tools.mcp_tools' * Find: os.path.exists("mcp_tools.py") * Replace with: os.path.exists("tools/mcp_tools.py") 4. Shell Commands in Strings: The hardcoded python commands need updating. * Find: from mcp_tools import (inside the -c "..." strings in discover_tools.py and modules/ascii_displays.py) * Replace with: from tools.mcp_tools import --- Step 3: Update Project Configuration The project's packaging configuration needs to be told that mcp_tools is no longer a top-level module. * Action: Edit pyproject.toml. * Change: In the py-modules list, remove "mcp_tools". The tools directory is a package (thanks to __init__.py) and will be handled correctly by the build system. --- Step 4: Solidify the `tools` Package This final code change makes the new structure robust and idiomatic. It tells Python that mcp_tools is a core part of the tools package. * Action: Edit tools/__init__.py. * Change: Add the following line to the file: ```python from . import mcp_tools ``` * Why? This ensures that the mcp_tools module is properly associated with the tools package, making imports more reliable and introspection easier. It also allows for potentially cleaner imports in the future, like from tools import mcp_tools. --- Verification After completing these steps, you should be able to test the success of the refactoring immediately. I recommend running: 1. .venv/bin/python discover_tools.py: This will be the quickest test to see if the discovery and import logic is working correctly. 2. .venv/bin/python cli.py mcp-discover: This will test the full integration through the cli.py entry point. This plan should allow you to execute the entire refactoring cleanly. I'll be here to help analyze any output or errors that arise. --- ## The Point of No Return: Moving the Monolith > This is it. I moved `mcp_tools.py` (the monolith) into the tools subfolder. > Everything's broken. Now I fix. **Me**: Okay, I've moved mcp_tools.py into tools. Give me the series of `rg | xargs sed` commands that I need to execute for step 2. **Gemini CLI**: Of course. Here is the sequence of commands for Step 2. Execute these one by one from your project root (/home/mike/repos/pipulate). They are designed to be safe, but it's always good practice to review the changes with git diff after running them. --- 1. Update import mcp_tools statements This command finds all files that directly import the mcp_tools module and rewrites the import to point to the new location, adding an as mcp_tools alias so the rest of the code in those files doesn't need to change. \rg -l --null '\bimport mcp_tools\b' | xargs -0 sed -i 's/import mcp_tools/import tools.mcp_tools as mcp_tools/g' --- 2. Update from mcp_tools import ... statements This handles all the cases where specific functions or variables are imported from mcp_tools. \rg -l --null 'from mcp_tools import' | xargs -0 sed -i 's/from mcp_tools import/from tools.mcp_tools import/g' --- 3. Update String Literals and Dynamic Imports This command specifically targets the sys.modules.get('mcp_tools') pattern and updates the string literal inside it. \rg -l --null "sys.modules.get('mcp_tools')" | xargs -0 sed -i "s/'mcp_tools'/'tools.mcp_tools'/g" --- 4. Update File Path Checks Finally, this updates the os.path.exists check to look for the file in its new tools/ directory location. The | character is used as a separator in sed here to avoid issues with the / in the path. 1 rg -l --null 'os.path.exists("mcp_tools.py")' | xargs -0 sed -i 's|"mcp_tools.py"|"tools/mcp_tools.py"|g' --- After running these commands, you will have completed the bulk of the code changes. You can then proceed with updating pyproject.toml and tools/__init__.py. --- **Me**: ```bash [mike@nixos:~/repos/pipulate]$ \rg -l --null "sys.modules.get('mcp_tools')" | xargs -0 sed -i "s/'mcp_tools'/'tools.mcp_tools'/g" sed: no input files ``` **Gemini CLI**: You are correct. My apologies. That command produced no input because the rg pattern was too specific and only looked for the .get() notation, failing to match the bracket notation ['...'] used elsewhere. However, this has highlighted a more significant issue. The previous commands were too broad and have likely created circular imports inside your newly moved tools/mcp_tools.py file by changing its own internal imports to point to itself (e.g., from tools.mcp_tools import ...). This will definitely break the application. Let's correct this with a two-part approach: first, we'll fix the damage, and then we'll proceed with the correct, more specific commands. --- Part A: Repair `tools/mcp_tools.py` The original self-import was likely an artifact that should be removed anyway. This command will find any incorrect, circular from tools.mcp_tools import ... lines within the file and delete them. sed -i '/from tools.mcp_tools import/d' tools/mcp_tools.py --- Part B: Resume Step 2 with Corrected Commands Now we can resume updating the string literals. Here are the corrected commands for what was previously Step 3 and 4. 3a. Update `sys.modules['...']` (Bracket Notation) This specifically targets the bracket notation that the previous command missed. \rg -l --null "sys.modules\['mcp_tools'\]" | xargs -0 sed -i "s/'mcp_tools'/'tools.mcp_tools'/g" 3b. Update `sys.modules.get('...')` (.get Notation) - Retry This is the command that previously found no files. It's possible the file it was targeting was the only one and has since been modified, but we'll run it again just in case. It is safe to run; if it finds nothing, it will do nothing. \rg -l --null "sys.modules.get('mcp_tools')" | xargs -0 sed -i "s/'mcp_tools'/'tools.mcp_tools'/g" 4. Update File Path Checks This command is the same as before and should still be run. \rg -l --null 'os.path.exists("mcp_tools.py")' | xargs -0 sed -i 's|"mcp_tools.py"|"tools/mcp_tools.py"|g' --- My apologies again for the error in the initial commands. This revised sequence should repair the issue and correctly handle all the necessary replacements. Please proceed with these, and I'll be ready for the next step. --- **Me**: [I show Gemini CLI all my commands.] **Gemini CLI**: Excellent, thank you for sharing the complete record. That's extremely helpful for verification. Let's walk through how to check if the surgery was a success. Based on your command history, it looks like the core changes were applied, but one of the commands reported sed: no input files when we expected it to find a match. This is a key area to investigate. Here is a 3-step process to verify your work: --- Step 1: The "Smoke Test" - Check for Lingering References Let's run your original rg command again. The output should be dramatically smaller and cleaner. rg mcp_tools What to look for: * GOOD: References inside the tools/ directory (e.g., from tools.mcp_tools import ...), comments, or documentation files (README.md). * BAD: Any lines like import mcp_tools or from mcp_tools import ... in your Python files (.py). If you see any of these, the sed command missed a file. --- Step 2: Manually Verify the "Missed" Change Your log shows that this command found nothing to change: \rg -l --null 'os.path.exists("mcp_tools.py")' | xargs -0 sed ... This is suspicious, as we expected it to find and change a line inside the mcp_tools.py file itself. Please manually check this. 1. Open the file: vim tools/mcp_tools.py 2. Go to the line: The original line was around 4389. 3. Check the code: You are looking for the line if os.path.exists("mcp_tools.py"). * If it still says "mcp_tools.py", please change it manually to "tools/mcp_tools.py". * If it was already changed somehow, then you're all set. --- Step 3: Functional Tests (The Ultimate Verification) If the code looks clean after the first two steps, it's time to see if the application still runs. These commands will test the entire import and discovery chain. 1. Test the discovery script directly: This is the quickest way to find import errors. 1 .venv/bin/python discover_tools.py 2. Test the CLI entry point: This confirms that cli.py can also find and use the tools. 1 .venv/bin/python cli.py mcp-discover If both of those commands run without raising an ImportError, you have successfully completed the most difficult part of the refactoring. The final steps would then be to update pyproject.toml and tools/__init__.py as we discussed. --- ## Verification and Validation: Proving the Surgery Was a Success > This might look like I'm still doing work but really it's getting a bunch of > output for validation that the surgery was a success. I'm telling Gemini CLI I > think I'm done and here's some proof of success. **Me**: Okay, I made the change to mcp_tools.py fixing the path. And... ```bash [mike@nixos:~/repos/pipulate]$ rg mcp_tools README.md 693:- Review `mcp_tools.py` for MCP protocol capabilities 1087: ├── mcp_tools.py # MCP protocol tools - the AI assistant interface 1385:mcp_tools.py # AI assistant interface pyproject.toml 46:py-modules = ["cli", "server", "common", "config", "ai_dictdb", "mcp_tools", "__init__"] tools/botify_tools.py 2:Botify MCP Tools - Extracted from mcp_tools.py for focused token optimization discover_tools.py 32: """Discover all MCP tools available in mcp_tools.py""" 34: # Import the mcp_tools module 36: import tools.mcp_tools as mcp_tools 38: print(f"❌ Error importing mcp_tools: {e}") 50: mcp_tools = [] 51: for name, obj in inspect.getmembers(sys.modules['tools.mcp_tools']): 56: mcp_tools.append(name) 69: for tool in sorted(mcp_tools): 105: for tool in mcp_tools: 107: func = getattr(sys.modules['tools.mcp_tools'], tool) 129: from tools.mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 132: register_all_mcp_tools() 156:.venv/bin/python -c "import asyncio; from tools.mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" 159:.venv/bin/python -c "import asyncio; from tools.mcp_tools import ai_capability_test_suite; result = asyncio.run(ai_capability_test_suite({'test_type': 'quick'})); print('Success Rate:', result.get('success_rate', 'N/A'), '%')" 162:.venv/bin/python -c "import asyncio; from tools.mcp_tools import ai_self_discovery_assistant; result = asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'})); print('Tools found:', result.get('total_tools_available', 'N/A'))" 165:.venv/bin/python -c "import asyncio; from tools.mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" tools/advanced_automation_tools.py 2:Advanced Automation & AI MCP Tools - Extracted from mcp_tools.py for token optimization 5:and AI training tools extracted from the monolithic mcp_tools.py. 7:Line range: 4830-7818 from original mcp_tools.py 35: from tools.mcp_tools import ( 47: return {"success": False, "error": "mcp_tools not available"} 387: from tools.mcp_tools import browser_hijack_workflow_complete 1863: "level": "2_mcp_tools", 1870: "level": "2_mcp_tools", 3021: 'mcp_tools_access': 'Four MCP tools for programmatic conversation management' modules/ai_tool_discovery_simple_parser.py 38:from tools.mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 176: register_all_mcp_tools() tools/mcp_tools.py 862:def register_all_mcp_tools(): 3895:# All tools are now registered in register_all_mcp_tools() function above 3926: register_all_mcp_tools() 3944: mcp_module = sys.modules.get('mcp_tools') 4078: "solution": "Check server startup logs, ensure tool is registered in register_all_mcp_tools()", 4290: mcp_result = await test_mcp_tools_availability() 4291: test_results["results"]["mcp_tools"] = mcp_result 4354:async def test_mcp_tools_availability() -> dict: 4365: "mcp_tools_accessible": True, 4379: "mcp_tools_accessible": True, 4386: if os.path.exists("tools/mcp_tools.py") and os.path.exists("server.py"): 4389: "mcp_tools_accessible": True, 4604: return await test_mcp_tools_availability() 4643: test_file = "mcp_tools.py" cli.py 82: from tools.mcp_tools import register_all_mcp_tools, MCP_TOOL_REGISTRY 83: register_all_mcp_tools() 160: from tools.mcp_tools import register_all_mcp_tools 161: register_all_mcp_tools() 163: # Import the server's registry - with inline architecture, we need to get it from mcp_tools 164: from tools.mcp_tools import MCP_TOOL_REGISTRY modules/ascii_displays.py 565: mcp_tools_count: int, 590: status_table.add_row("🔧 MCP Tools", "✅ Ready", f"{mcp_tools_count} tools available") 602: commands_table.add_row("🎭 Session Hijack", ".venv/bin/python -c \"import asyncio; from tools.mcp_tools import execute_complete_session_hijacking; asyncio.run(execute_complete_session_hijacking({}))\"") 603: commands_table.add_row("🧠 AI Discovery", ".venv/bin/python -c \"from tools.mcp_tools import ai_self_discovery_assistant; import asyncio; asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'}))\"") 634:✅ MCP Tools: {mcp_tools_count} tools available modules/server_logging.py 147: # 🔧 FINDER_TOKEN: MAX_ROLLED_LOOKING_AT_DIRS moved to mcp_tools.py (used by rotate_looking_at_directory) server.py 71:import tools.mcp_tools as mcp_tools 85:from tools.mcp_tools import register_all_mcp_tools 88:# Initialize MCP_TOOL_REGISTRY before importing mcp_tools to avoid circular dependency issues 102:# Pass our registry to mcp_tools so they use the same instance 103:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 174:# 🔧 FINDER_TOKEN: rotate_looking_at_directory moved to mcp_tools.py to eliminate circular imports 401:# Initialize MCP_TOOL_REGISTRY before importing mcp_tools to avoid circular dependency issues 404:# Pass our registry to mcp_tools so they use the same instance 405:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 724:# 🔧 FINDER_TOKEN: register_mcp_tool moved to mcp_tools.py (superior error handling) 725:# Use register_mcp_tool from mcp_tools.py - it has better error handling for uninitialized registry 727:# MCP tools are now consolidated in mcp_tools.py - see register_all_mcp_tools() 731:# Tools now registered via register_all_mcp_tools() from mcp_tools.py 736:# _pipeline_state_inspector, etc.) have been moved to mcp_tools.py for better organization. 737:# See register_all_mcp_tools() in mcp_tools.py for complete tool registration. 739:# 🔧 FINDER_TOKEN: _read_botify_api_token moved to mcp_tools.py to eliminate duplication 742:# All Botify MCP tools moved to mcp_tools.py for better maintainability: 749:# ALL Botify tools are now registered via register_all_mcp_tools() in mcp_tools.py: 756:# are now registered via register_all_mcp_tools() in mcp_tools.py 758:# are in mcp_tools.py. The simple duplicate versions have been removed from server.py. 762:# are now registered via register_all_mcp_tools() in mcp_tools.py 4402:# Ensure mcp_tools has the correct registry reference 4403:mcp_tools.MCP_TOOL_REGISTRY = MCP_TOOL_REGISTRY 4404:register_all_mcp_tools() 4438: mcp_tools_count=tool_count, 7161: "available_mcp_tools": { plugins/130_gap_analysis.py 493: from tools.mcp_tools import browser_scrape_page, browser_analyze_scraped_page assets/pipulate-init.js 1909:- mcp_tools.py (MCP tool definitions) browser_automation/automation_recipes/README_SAVE_LOAD_AUTOMATION.md 202:from tools.mcp_tools import browser_save_all_data_single_session 209:from tools.mcp_tools import browser_load_all_data_single_session [mike@nixos:~/repos/pipulate]$ ``` And also: ```bash [mike@nixos:~/repos/pipulate]$ .venv/bin/python discover_tools.py 🚀 MCP TOOLS DISCOVERY SCRIPT ================================================== 🔍 ENVIRONMENT CHECK: Python executable: /home/mike/repos/pipulate/.venv/bin/python Virtual env: Not detected ✅ Using virtual environment ⚠️ FINDER_TOKEN: KEYCHAIN_IMPORT_FAILED - AI Keychain not available 🔧 MCP TOOLS DISCOVERY RESULTS ================================================== 📂 Core Tools (19 tools): • _read_botify_api_token • _run_context_aware_test_suite • pipeline_state_inspector • test_basic_browser_capability • test_botify_actual_connectivity • test_botify_connectivity • test_environment_access • test_file_system_access • test_log_access • test_mcp_registry • test_mcp_registry_context_aware • test_mcp_tools_availability • test_pipeline_functionality • test_pipeline_inspection • test_pipeline_inspection_context_aware • test_specific_tool • test_ui_accessibility • test_ui_interaction • test_ui_interaction_context_aware 📂 Botify API (6 tools): • botify_execute_custom_bql_query • botify_get_full_schema • botify_list_available_analyses • botify_list_projects • botify_ping • botify_simple_query 📂 Local LLM (4 tools): • local_llm_get_context • local_llm_grep_logs • local_llm_list_files • local_llm_read_file 📂 Browser Automation (5 tools): • browser_analyze_scraped_page • browser_automate_instructions • browser_automate_workflow_walkthrough • browser_interact_with_current_page • browser_scrape_page 📂 UI Interaction (2 tools): • ui_flash_element • ui_list_elements 📂 AI Discovery (2 tools): • ai_capability_test_suite • ai_self_discovery_assistant 📂 Session Hijacking (1 tools): • execute_ai_session_hijacking_demonstration 🎯 TOTAL TOOLS DISCOVERED: 39 🧪 FUNCTION ACCESS TEST: ✅ _read_botify_api_token: Accessible ✅ _run_context_aware_test_suite: Accessible ✅ ai_capability_test_suite: Accessible ✅ ai_self_discovery_assistant: Accessible ✅ botify_execute_custom_bql_query: Accessible ✅ botify_get_full_schema: Accessible ✅ botify_list_available_analyses: Accessible ✅ botify_list_projects: Accessible ✅ botify_ping: Accessible ✅ botify_simple_query: Accessible ✅ browser_analyze_scraped_page: Accessible ✅ browser_automate_instructions: Accessible ✅ browser_automate_workflow_walkthrough: Accessible ✅ browser_interact_with_current_page: Accessible ✅ browser_scrape_page: Accessible ✅ execute_ai_session_hijacking_demonstration: Accessible ✅ local_llm_get_context: Accessible ✅ local_llm_grep_logs: Accessible ✅ local_llm_list_files: Accessible ✅ local_llm_read_file: Accessible ✅ pipeline_state_inspector: Accessible ✅ test_basic_browser_capability: Accessible ✅ test_botify_actual_connectivity: Accessible ✅ test_botify_connectivity: Accessible ✅ test_environment_access: Accessible ✅ test_file_system_access: Accessible ✅ test_log_access: Accessible ✅ test_mcp_registry: Accessible ✅ test_mcp_registry_context_aware: Accessible ✅ test_mcp_tools_availability: Accessible ✅ test_pipeline_functionality: Accessible ✅ test_pipeline_inspection: Accessible ✅ test_pipeline_inspection_context_aware: Accessible ✅ test_specific_tool: Accessible ✅ test_ui_accessibility: Accessible ✅ test_ui_interaction: Accessible ✅ test_ui_interaction_context_aware: Accessible ✅ ui_flash_element: Accessible ✅ ui_list_elements: Accessible 🎯 ACCESSIBLE FUNCTIONS: 39/39 🔧 TOOL REGISTRATION TEST: ⚠️ FINDER_TOKEN: KEYCHAIN_TOOLS_SKIPPED - AI Keychain not available ✅ MCP_TOOL_REGISTRY exists with 28 entries 💡 WORKING DISCOVERY COMMANDS: ================================================== # Command 1: List all MCP tool functions .venv/bin/python discover_tools.py # Command 2: Test specific tool (use exact function name) .venv/bin/python -c "import asyncio; from tools.mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" # Command 3: Test capability suite (shell-safe) .venv/bin/python -c "import asyncio; from tools.mcp_tools import ai_capability_test_suite; result = asyncio.run(ai_capability_test_suite({'test_type': 'quick'})); print('Success Rate:', result.get('success_rate', 'N/A'), '%')" # Command 4: Test self-discovery (shell-safe) .venv/bin/python -c "import asyncio; from tools.mcp_tools import ai_self_discovery_assistant; result = asyncio.run(ai_self_discovery_assistant({'discovery_type': 'capabilities'})); print('Tools found:', result.get('total_tools_available', 'N/A'))" # Command 5: Test environment access (no parameters needed) .venv/bin/python -c "import asyncio; from tools.mcp_tools import test_environment_access; result = asyncio.run(test_environment_access()); print('Environment Test Result:', result)" ✅ DISCOVERY COMPLETE! 📊 Summary: 39 tools found, 39 accessible 🔧 Registration: Working [mike@nixos:~/repos/pipulate]$ .venv/bin/python cli.py mcp-discover ╭───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ 🚀 Pipulate :: The Local-First AI SEO & Automation Workshop 🚀 │ ╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ ╭───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ 🔧 MCP Tools Discovery │ ╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ ╭───────────────────────────────────────────────────────── 🎯 The Golden Path - Rule of 7 ──────────────────────────────────────────────────────────╮ │ ✨ Essential MCP Tools (Getting Started) │ │ │ │ These 7 core tools provide the foundation for AI collaboration. │ │ Master these first before exploring the full toolkit. │ ╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ 1. ai_self_discovery_assistant 2. ai_capability_test_suite 3. browser_scrape_page 4. browser_analyze_scraped_page 5. local_llm_list_files 6. local_llm_read_file 7. pipeline_state_inspector Use `.venv/bin/python cli.py mcp-discover --all` to see all available tools. Use `.venv/bin/python cli.py mcp-discover --tool ` for detailed info on a specific tool. ╭──────────────────────────────────────────────────────────── 🚀 Recommended Next Steps ────────────────────────────────────────────────────────────╮ │ 🎯 Golden Path Workflow: │ │ │ │ 1. .venv/bin/python cli.py call ai_capability_test_suite - Verify your environment │ │ 2. .venv/bin/python cli.py call ai_self_discovery_assistant - Understand the system │ │ 3. .venv/bin/python cli.py call --json-args '{"param": "value"}' - Execute tasks │ ╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ [mike@nixos:~/repos/pipulate]$ ``` --- ## The Final Polish: Consolidating the New Plugin System > Gemini confirms that this is a success. Wow, to have done this entire thing > with Gemini CLI and vim again after months with Cursor AI is such a relief. > It's a huge validation that I can get that infernal VSCode way of working out > of my system even after allowing myself to get infected by it. **Gemini CLI**: This is a resounding success. The output from your functional tests is the best possible news. Let's break it down: 1. `rg mcp_tools`: The "smoke test" looks great. All the critical Python files (server.py, cli.py, discover_tools.py) have been correctly updated to reference tools.mcp_tools. This is exactly what we wanted to see. 2. `discover_tools.py`: This is the definitive proof. It ran without any ImportError, found all 39 tools from the new location, and even generated the correct "WORKING DISCOVERY COMMANDS" with the new from tools.mcp_tools import ... path. 3. `cli.py mcp-discover`: This confirms the front-end CLI is also working perfectly with the new structure. You have successfully completed the most difficult part of the refactoring. The core logic of your application has adapted to the new, cleaner structure. Final Cleanup (Steps 3 & 4) You are just two small steps away from completing the plan. Your rg output shows two files that still need minor adjustments: 1. `pyproject.toml`: This file still lists "mcp_tools" as a top-level module. This should be removed. 2. `tools/mcp_tools.py`: It still has a couple of incorrect self-references (e.g., sys.modules.get('mcp_tools') and test_file = "mcp_tools.py"). After that, the final touch is to edit tools/__init__.py to officially integrate the module into the package. You've done the heavy lifting. Shall I guide you through these last few cleanup steps, starting with pyproject.toml? --- ## Letting Gemini CLI Go Into Agentic Mode **Me**: Excellent! And yes, please. > After the first round of work where I basically told Gemini CLI to tell me > what to do so that I could go and do it myself with CLI-based search and > replaces, this is me allowing Gemini CLI to do some of the final clean-up work > itself. I feel okay about this because I have a firm grip on the reins again. > It no longer feels like a wagon careening out of control. **Gemini CLI**: ``` ✦ Excellent. Let's start with pyproject.toml. First, I'll read the file to get its current content. ╭─────────────────────────────╮ │ ✓ ReadFile pyproject.toml │ ╰─────────────────────────────╯ ✦ Okay, I have the content. I will now remove "mcp_tools" from the py-modules list. ╭─────────────────────────────────────────────────────────────────────────────────────────────────╮ │ ✓ Edit pyproject.toml: py-modules = ["cli", "server",... => py-modules = ["cli", "server",... │ │ │ │ 43 pipulate = "cli:main" │ │ 44 │ │ 45 [tool.setuptools] │ │ 46 - py-modules = ["cli", "server", "common", "config", "ai_dictdb", "mcp_tools", │ │ "__init__"] │ │ 46 + py-modules = ["cli", "server", "common", "config", "ai_dictdb", "__init__"] │ │ 47 │ │ 48 [tool.setuptools.packages.find] │ │ 49 where = ["."] │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────╯ ✦ Excellent. pyproject.toml is now correct. Next, I'll fix the two remaining incorrect self-references inside tools/mcp_tools.py. First, I will correct the sys.modules.get('mcp_tools') line to point to the new module path. ╭─────────────────────────────────────────────────────────────────────────────────────────────────╮ │ ✓ Edit tools/mcp_tools.py: mcp_module = sys.m... => mcp_module = sys.… │ │ │ │ 3941 # Get all functions that are MCP tool handlers (test functions and main │ │ tools) │ │ 3942 import inspect │ │ 3943 import sys │ │ 3944 - mcp_module = sys.modules.get('mcp_tools') │ │ 3944 + mcp_module = sys.modules.get('tools.mcp_tools') │ │ 3945 if mcp_module: │ │ 3946 for name, obj in inspect.getmembers(mcp_module): │ │ 3947 if (callable(obj) and │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────╯ ✦ Good. That's one down. Now for the last reference inside that file. I'll update the test_file variable to use the correct path. ╭─────────────────────────────────────────────────────────────────────────────────────────────────╮ │ ✓ Edit tools/mcp_tools.py: test_file = "mcp_tools... => test_file = "tools/mc… │ │ │ │ 4640 from pathlib import Path │ │ 4641 │ │ 4642 # Test reading a simple file │ │ 4643 - test_file = "mcp_tools.py" │ │ 4643 + test_file = "tools/mcp_tools.py" │ │ 4644 if os.path.exists(test_file): │ │ 4645 with open(test_file, 'r') as f: │ │ 4646 content = f.read(100) # Just first 100 chars │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────╯ ✦ Perfect. The tools/mcp_tools.py file is now fully corrected. We have now completed all the necessary code and configuration changes. The final action is to officially integrate the mcp_tools module into the tools package. This makes the structure more robust and idiomatic. I will do this by adding from . import mcp_tools to the tools/__init__.py file. First, I'll read the file. ╭────────────────────────────────╮ │ ✓ ReadFile tools/__init__.py │ ╰────────────────────────────────╯ ✦ Okay, I see the current structure. I will add the new import statement right after the docstring to integrate mcp_tools.py into the package. ╭───────────────────────────────────────────────────────────────────────────────────────╮ │ ✓ Edit tools/__init__.py: """... => """... │ │ │ │ 4 This package contains extracted MCP tools organized by domain for token │ │ optimization. │ │ 5 """ │ │ 6 │ │ 7 + from . import mcp_tools │ │ 8 + │ │ 9 # Re-export commonly used functions for convenience │ │ 10 try: │ │ 11 from .botify_tools import ( │ ╰───────────────────────────────────────────────────────────────────────────────────────╯ ✦ That's it. The final step is complete. To summarize, we have: 1. Successfully moved mcp_tools.py into the tools/ directory. 2. Updated all imports and references throughout the project to point to the new location. 3. Corrected the pyproject.toml configuration. 4. Solidified the tools directory into a proper Python package. You now have a single, logical location for all your tools under the tools/ directory, paving the way for the clean, discoverable plugin system you envisioned. The refactoring is complete. I would recommend committing these latest changes. What would you like to tackle next? ``` --- ## Git Branch Takeover Practice > The work is done but it's all in an experimential main branch named > *normalize* that I still have to push back into the *main* branch and it's not > natural to me yet, so I will keep spelling it out until it feels automatic to > me. Okay, I want to keep merging my experimental branches like this *normalize* one back into the git main branch. I want to call it *merging it in* because that's the concept that comes naturally but that's not really it. I'm doing a *git branch takeover* again like a few articles ago. Let's first establish what branch we're on. I did a recent push to the remote origin so the branch work is safe offsite. I also did a `nix develop .#dev` out of an abundance of caution to make sure the new work didn't interfere with the installation process — an oversight I've done in the recent past. ```bash [mike@nixos:~/repos/pipulate]$ git branch main * normalize [mike@nixos:~/repos/pipulate]$ ``` I forcibly rename my *normalize* branch to main: ```bash [mike@nixos:~/repos/pipulate]$ git branch -M normalize main [mike@nixos:~/repos/pipulate]$ git branch * main [mike@nixos:~/repos/pipulate]$ ``` I forcibly push it upstream with the remote name *main*: ```bash [mike@nixos:~/repos/pipulate]$ git push --force origin main Total 0 (delta 0), reused 0 (delta 0), pack-reused 0 (from 0) To github.com:miklevin/pipulate eedce9c..d401483 main -> main [mike@nixos:~/repos/pipulate]$ ``` Next I delete the old upstream remote *normalize*: ```bash [mike@nixos:~/repos/pipulate]$ git push origin --delete normalize To github.com:miklevin/pipulate - [deleted] normalize [mike@nixos:~/repos/pipulate]$ ``` I seem to hit a snafu when I do this: ```bash [mike@nixos:~/repos/pipulate]$ git push fatal: The current branch main has multiple upstream branches, refusing to push. [mike@nixos:~/repos/pipulate]$ git push -u origin main warning: branch.main.remote has multiple values warning: branch.main.merge has multiple values branch 'main' set up to track 'origin/main'. Everything up-to-date [mike@nixos:~/repos/pipulate]$ git push fatal: The current branch main has multiple upstream branches, refusing to push. ``` And so I checked with Gemini and there's these 2 commands: git config --unset-all branch.main.remote git config --unset-all branch.main.merge ...that will fix it: ```bash [mike@nixos:~/repos/pipulate]$ git config --unset-all branch.main.remote git config --unset-all branch.main.merge [mike@nixos:~/repos/pipulate]$ git push branch 'main' set up to track 'origin/main'. Everything up-to-date [mike@nixos:~/repos/pipulate]$ ``` And that's it. Taking over the main branch with a recently successful experimental branch is a process that I definitely need to get better and probably document somewhere that's right at my fingertips so I don't have to struggle to re-figure it out every time. But overall this has been a massive step forward. I have all the tool-calling stuff — whether you really want to call it MCP or not at this point is debatable — gathered into tools folder. I have the two parallel systems still running in parallel and side-by-side but at least both out of the same folder now. I still have some tool registry stuff to figure out. Maybe help me enumerate these last points about tool registry and discovery and such which I believe if I understood you is working correctly for the tools in mcp_tools but not the broken out plugin style ones. --- ## Planning MCP Tool Discovery & Registration > All that was just getting `mcp_tools.py` into the same folder as the > burgeoning mcp plugin system. I still have to turn it into auto-discovering > and registering components. This is Gemini and me formulating the next-steps. **Gemini CLI**: Excellent work on the branch takeover. That's a powerful git workflow, and you've documented the exact commands needed to resolve the tricky "multiple upstreams" issue, which is a fantastic piece of knowledge to have at your fingertips. You've successfully consolidated all the tool-related code into the tools/ folder, which was the primary goal of this major refactoring. Now, for your final question about the tool registry and discovery. You're absolutely right to focus on this, as it's the final piece of the puzzle. However, I need to clarify one crucial detail about how the system works right now, which will illuminate the path forward. You mentioned: "...if I understood you is working correctly for the tools in mcp_tools but not the broken out plugin style ones." It's actually the other way around: the discovery is only working because of tools/mcp_tools.py. Your discovery script (discover_tools.py) and server startup logic are hardwired to look at that one specific file. The tools in botify_tools.py and advanced_automation_tools.py are only being registered because tools/mcp_tools.py imports them. This means you don't have a true plugin system yet. You have a monolith that has been moved and is importing its neighbors. So, to get to the simple, robust plugin system you want, here are the final enumerated points—the concrete next steps. --- ### The Path to a True Plugin System The goal is to make the system smart enough to automatically discover any tool in any file within the tools/ directory, without needing to be told about it in mcp_tools.py. 1. Implement Automatic Discovery Logic The current logic explicitly imports tools.mcp_tools. This needs to be replaced with code that scans the tools directory. * Where to Change: In discover_tools.py and server.py (at startup, where register_all_mcp_tools is currently called). * What to Do: Replace the static import with dynamic logic that: 1. Iterates through all *.py files in the tools/ directory. 2. Uses a library like importlib to load each file as a Python module. 2. Create a Tool Decorator (`@mcp_tool`) This is the "easy button" that makes the whole system work. Instead of a giant register_all_mcp_tools function, you'll use a decorator to mark functions as tools. * Where to Define: A great place would be tools/__init__.py. * What it Looks Like: ```python # In tools/__init__.py MCP_TOOL_REGISTRY = {} def mcp_tool(func): """Decorator to automatically register a function as an MCP tool.""" print(f"🔧 Registering tool: {func.__name__}") MCP_TOOL_REGISTRY[func.__name__] = func return func ``` 3. Refactor to Use the Decorator Once the decorator exists and the discovery logic is in place, the final step is to apply it. * What to Do: 1. Go through tools/mcp_tools.py, tools/botify_tools.py, etc. 2. Add the @mcp_tool decorator directly above every function that should be a tool (e.g., above async def browser_scrape_page(...)). 3. Delete the entire `register_all_mcp_tools()` function. Its job is now obsolete. The new discovery logic and the decorator handle everything automatically. --- Once you complete these three steps, you will have achieved your goal. Adding a new tool will be as simple as creating a new function in a new or existing file in the tools/ directory and adding @mcp_tool to it. The system will find and register it on its own. --- ## Another Brain Rest Pshwew! Okay, not bad for coming back from a Saturday afternoon break. If I play my cards right I will have turned this into a true plugin system by the end of the day. That is my goal. I don't think I will have "deconstructed" the monolith by that time, but I do think it will *also* be a proper "mcp" tool plugin system by that time. And the whole mental model of this system is clarifying. The original Pipulate system that I envisioned as really a way to run Web Apps that idiomatically reflect how Jupyter Notebooks work but with an AI running shotgun to walk you through it and without having to see the Python code has evolved into so much more. The trick is to allow it to continue evolving into so much more but the code *looking like* so much less. The more time I spend the *simpler* it should all appear even if there is quite a bit of complexity lurking under the surface. ## Book Analysis This analysis transforms the provided journal entry into structured, book-ready components, focusing on clarifying its core technical insights and shaping its narrative potential. --- **Crafting Compelling Narratives: Title & Filename Brainstorm:** * **Title Option 1:** The Monolith and the Module: A Pragmatic Refactoring Story * **Filename:** `monolith-module-python-refactoring.md` * **Rationale:** This title frames the entry as a relatable story about a classic software architecture decision. It appeals to developers who have faced the choice between monolithic and modular designs. * **Title Option 2:** AI-Assisted Surgery: Refactoring a Core System with Gemini CLI * **Filename:** `ai-assisted-refactoring-gemini-cli.md` * **Rationale:** This title highlights the unique human-AI collaboration aspect, attracting readers interested in the future of software development and the practical application of AI coding assistants. * **Title Option 3:** Command-Line Mastery: A Live Session on `rg`, `sed`, and `git` for Major Refactoring * **Filename:** `command-line-refactoring-rg-sed-git.md` * **Rationale:** This is a skills-focused title that targets developers looking to improve their command-line proficiency. It promises a practical, hands-on demonstration of powerful tools. * **Preferred Option:** * **Title (plain text for YAML):** From Monolith to Plugins: An AI-Assisted Architectural Refactor * **Filename:** `ai-assisted-monolith-to-plugin-refactor.md` * **Rationale:** This title is the most comprehensive and compelling. "From Monolith to Plugins" is a classic, understandable transformation, while "AI-Assisted" captures the unique, modern methodology. It promises a story, a technical lesson, and a glimpse into a new way of working. --- **Book Potential Analysis:** * **Strengths as Book Fodder:** * **Extreme Transparency:** The entry provides an unfiltered, command-by-command look at a complex refactoring process, including errors (`sed: no input files`) and corrections. This authenticity is rare and highly valuable for teaching. * **Practical Skill Demonstration:** It's a masterclass in using powerful command-line tools (`rg`, `xargs`, `sed`, `git`) for real-world, high-stakes software surgery, moving beyond trivial examples. * **Clear Strategic Thinking:** The author clearly articulates the "why" behind every step, from the initial architectural decision to the detailed planning with the AI assistant. * **Novel Git Workflow:** The documentation of the "git branch takeover" and the fix for the "multiple upstreams" error is a specific, reusable lesson that solves a common and frustrating `git` problem. * **Opportunities for Enrichment (for Book Adaptation):** * **Create a "CLI Power Moves" Box:** Isolate the `rg | xargs sed` and `git config --unset-all` command sequences into a formatted callout box to make them easy for readers to find and reference. * **Visualize the Refactor:** Add a simple "Before/After" file tree diagram to visually represent the architectural change of moving `mcp_tools.py` into the `tools/` directory. * **Add an Explanatory Note on Decorators:** When mentioning the `@mcp_tool` decorator, include a brief paragraph explaining what a Python decorator is and why it's a perfect tool for creating a clean plugin system. --- **AI Editorial Perspective: From Journal to Chapter:** This entry is an outstanding case study that could anchor a chapter on **"Modern Software Craftsmanship"** or **"AI-Augmented Development."** Its real power lies in its detailed, blow-by-blow account of a process that is usually hidden from view. Most technical books present the clean, final result; this entry shows the messy, iterative, and intellectually rigorous *work* of getting there. It's a perfect illustration of how a senior developer thinks, blending high-level architectural philosophy with deep, in-the-weeds command-line execution. The human-AI dynamic is particularly compelling. This is not a case of a human asking an AI to "write me some code." Instead, the human performs the initial analysis, presents the findings to the AI, and requests a strategic plan. The AI acts as an expert consultant, providing a clear, phased blueprint for the refactoring. The human then executes that plan, using their own superior skills in `vim` and the command line, and reports back the results, including errors. The AI then helps debug and refine the process. This symbiotic relationship—human as strategist and skilled operator, AI as planner and verifier—is a sophisticated and realistic model for the future of programming that would be immensely valuable to showcase in a book. --- **Suggested Next AI Processing Steps:** 1. **Task Suggestion 1:** Generate the Plugin Discovery Code * **Potential Prompt Snippet for Next AI:** "Based on the final plan to create a true plugin system, write a Python function named `discover_and_register_tools`. This function should scan the `tools/` directory, use `importlib` to dynamically load all `.py` modules, and rely on an `@mcp_tool` decorator to populate a central registry. Include detailed comments for a book." 2. **Task Suggestion 2:** Create a Tutorial on the "Git Branch Takeover" * **Potential Prompt Snippet for Next AI:** "Using the author's terminal log as a reference, write a concise, step-by-step tutorial titled 'How to Safely Replace `main` with an Experimental Branch.' Explain each command (`git branch -M`, `git push --force`, `git push --delete`, and the `git config --unset-all` fix) and the rationale behind the workflow."