Add persistent memory to Claude, Cursor, Windsurf, and other AI assistants using the Model Context Protocol (MCP).
## What is this? This MCP server connects your AI assistant to [Memphora](https://memphora.ai), giving it the ability to: - **Remember** information across conversations - **Search** your personal knowledge base - **Extract** insights from conversations automatically - **Recall** your preferences, facts, and context ## Quick Start ### 1. Install ```bash # Using pip pip install memphora-mcp # Or using uvx (recommended for Claude Desktop) uvx memphora-mcp ``` ### 2. Get Your API Key 1. Go to [memphora.ai/dashboard](https://memphora.ai/dashboard) 2. Create an account or sign in 3. Copy your API key from the dashboard ### 3. Configure Claude Desktop Add to your Claude Desktop config file: **macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json` **Windows:** `%APPDATA%\Claude\claude_desktop_config.json` ```json { "mcpServers": { "memphora": { "command": "uvx", "args": ["memphora-mcp"], "env": { "MEMPHORA_API_KEY": "your_api_key_here", "MEMPHORA_USER_ID": "your_unique_user_id" } } } } ``` ### 4. Restart Claude Desktop Close and reopen Claude Desktop. You should see the Memphora tools available! ## Usage Examples ### Storing Memories Just tell Claude something about yourself: ``` You: "I work at Google as a software engineer" Claude: [stores memory] "Got it! I'll remember that you work at Google as a software engineer." You: "My favorite programming language is Python" Claude: [stores memory] "Noted! I'll remember that Python is your favorite programming language." ``` ### Recalling Memories Ask Claude about things you've told it before: ``` You: "Where do I work?" Claude: [searches memories] "You work at Google as a software engineer." You: "What programming languages do I like?" Claude: [searches memories] "Your favorite programming language is Python." ``` ### Automatic Context Claude will automatically search your memories when relevant: ``` You: "Can you help me with some code?" Claude: [searches memories for context] "Sure! Since you prefer Python and work at Google, I'll write this in Python following Google's style guide..." ``` ## Available Tools | Tool | Description | |------|-------------| | `memphora_search` | Search memories for relevant information | | `memphora_store` | Store new information for future recall | | `memphora_extract_conversation` | Extract memories from a conversation | | `memphora_list_memories` | List all stored memories | | `memphora_delete` | Delete a specific memory | ## Configuration Options | Environment Variable | Description | Default | |---------------------|-------------|---------| | `MEMPHORA_API_KEY` | Your Memphora API key | Required | | `MEMPHORA_USER_ID` | Unique identifier for your memories | `mcp_default_user` | ## Using with Other MCP Clients ### Cursor Add to your Cursor settings: ```json { "mcp": { "servers": { "memphora": { "command": "uvx", "args": ["memphora-mcp"], "env": { "MEMPHORA_API_KEY": "your_api_key_here" } } } } } ``` ### Windsurf Add to your Windsurf MCP configuration: ```json { "mcpServers": { "memphora": { "command": "python", "args": ["-m", "memphora_mcp"], "env": { "MEMPHORA_API_KEY": "your_api_key_here" } } } } ``` ## Development ### Running Locally ```bash # Clone the repo git clone https://github.com/Memphora/memphora-mcp.git cd memphora-mcp # Install dependencies pip install -e ".[dev]" # Set your API key export MEMPHORA_API_KEY="your_key" # Run the server python -m memphora_mcp ``` ### Testing ```bash pytest tests/ ``` ## Privacy & Security - Your memories are stored securely in Memphora's cloud - Each user has isolated memory storage - API keys are stored locally on your machine - All communication is encrypted via HTTPS ## Support - Documentation: [memphora.ai/docs](https://memphora.ai/docs) - Issues: [GitHub Issues](https://github.com/Memphora/memphora-mcp/issues) - Email: support@memphora.ai ## License MIT License - see [LICENSE](LICENSE) for details.