# Awesome AI Agents [![Awesome](https://awesome.re/badge.svg)](https://awesome.re) _A curated list of frameworks, tools, libraries, platforms, and resources for building and deploying AI agents._

**Built by the community** — add your project

--- ## Contents - [🌟 Core Frameworks](#-core-frameworks) - [🚀 Specialized Agents](#-specialized-agents) - [💻 Coding Agents](#-coding-agents) - [🔬 Research Agents](#-research-agents) - [🎨 Creative Agents](#-creative-agents) - [🌐 Web & Computer Use Agents](#-web--computer-use-agents) - [🗣️ Programming Language Agents](#-programming-language-agents) - [🎙️ Voice Agents](#-voice-agents) - [⚙️ Agent Operations](#-agent-operations) - [🧠 Memory](#-memory) - [📊 Evaluation](#-evaluation) - [📈 Observability](#-observability) - [🚀 Deployment](#-deployment) - [🔒 Security & Governance](#-security--governance) - [🔌 Protocols](#-protocols) - [📚 Research & Benchmarks](#-research--benchmarks) - [📄 Papers](#-papers) - [📊 Benchmarks](#-benchmarks) - [🌐 Community Resources](#-community-resources) - [👥 Communities](#-communities) - [📰 Newsletters](#-newsletters) - [🚀 Contributors](#-contributors) --- ## 🌟 Core Frameworks Frameworks for building and managing AI agents. | Framework | Stars | Description | | -------------------------------------------------------------------------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | [AutoGen](https://github.com/microsoft/autogen) | ![](https://img.shields.io/github/stars/microsoft/autogen) | Multi-agent conversations, GPT-4 integration, customizable workflows | | [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT) | ![](https://img.shields.io/github/stars/Significant-Gravitas/AutoGPT) | Autonomous AI agent for task completion, web browsing, and code execution | | [MetaGPT](https://github.com/FoundationAgents/MetaGPT) | ![](https://img.shields.io/github/stars/FoundationAgents/MetaGPT) | Simulates software company workflows, role-based agents | | [Neurolink](https://github.com/juspay/neurolink) | ![](https://img.shields.io/github/stars/juspay/neurolink) | Multi-provider AI agent framework, unifies 12+ LLM providers, workflow orchestration | | [CrewAI](https://github.com/crewAIInc/crewAI) | ![](https://img.shields.io/github/stars/crewAIInc/crewAI) | Role-based agent orchestration, task delegation | | [PraisonAI](https://github.com/MervinPraison/PraisonAI) | ![](https://img.shields.io/github/stars/MervinPraison/PraisonAI) | Fastest multi-agent framework (3.77μs), 100+ LLMs, MCP, workflows, Python & JS SDKs | | [LightAgent](https://github.com/wanxingai/LightAgent) | ![](https://img.shields.io/github/stars/wanxingai/LightAgent) | Lightweight Python agent framework with memory, MCP/SSE, Skills, streaming, and LightSwarm multi-agent collaboration | | [LangChain](https://github.com/langchain-ai/langchain) | ![](https://img.shields.io/github/stars/langchain-ai/langchain) | Tool integration, memory management, agent chaining | | [LangGraph](https://github.com/langchain-ai/langgraph) | ![](https://img.shields.io/github/stars/langchain-ai/langgraph) | Stateful, multi-actor applications with LLMs | | [SuperAGI](https://github.com/TransformerOptimus/SuperAGI) | ![](https://img.shields.io/github/stars/TransformerOptimus/SuperAGI) | Open-source AGI framework, multi-modal agents | | [Google ADK (Agent Development Kit)](https://github.com/google/adk-python) | ![](https://img.shields.io/github/stars/google/adk-python) | Code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents | | [OpenAI Assistants API (SDK)](https://github.com/openai/openai-python) | ![](https://img.shields.io/github/stars/openai/openai-python) | Build AI assistants with tools and persistent threads via SDK | | [AgentOps](https://github.com/AgentOps-AI/agentops) | ![](https://img.shields.io/github/stars/AgentOps-AI/agentops) | Monitoring, cost tracking, and benchmarking SDK for agents | | [AgentField](https://github.com/Agent-Field/agentfield) | ![](https://img.shields.io/github/stars/Agent-Field/agentfield) | Open-source control plane for AI agents at scale, with routing, memory, observability, identity, and auth | | [Agentset](https://github.com/agentset-ai/agentset) | ![](https://img.shields.io/github/stars/agentset-ai/agentset) | Production-ready RAG platform with agentic reasoning, hybrid search, and multimodal support | | [LLMStack](https://github.com/trypromptly/LLMStack) | ![](https://img.shields.io/github/stars/trypromptly/LLMStack) | No-code multi-agent framework with data workflows | | [Agency Swarm](https://github.com/VRSEN/agency-swarm) | ![](https://img.shields.io/github/stars/VRSEN/agency-swarm) | Reliable multi-agent orchestration using OpenAI Assistants API | | [AGiXT](https://github.com/Josh-XT/AGiXT) | ![](https://img.shields.io/github/stars/Josh-XT/AGiXT) | Adaptive automation platform with persistent memory | | [Upsonic](https://github.com/Upsonic/Upsonic) | ![](https://img.shields.io/github/stars/Upsonic/Upsonic) | Reliability layer, model context protocol, task-oriented | | [Taskade](https://github.com/taskade/taskade) | ![](https://img.shields.io/github/stars/taskade/taskade) | AI-native workspace for building and deploying multi-agent workflows | | [Taskade MCP](https://github.com/taskade/mcp) | ![](https://img.shields.io/github/stars/taskade/mcp) | Open-source MCP toolkit and integrations for building AI agents and automated workflows | | [AgentVerse](https://github.com/OpenBMB/AgentVerse) | ![](https://img.shields.io/github/stars/OpenBMB/AgentVerse) | Multi-agent simulation environments for research | | [ChatDev](https://github.com/OpenBMB/ChatDev) | ![](https://img.shields.io/github/stars/OpenBMB/ChatDev) | Collaborative software development agents | | [Agno](https://github.com/agno-agi/agno) | ![](https://img.shields.io/github/stars/agno-agi/agno) | Multi-agent framework, runtime, and control plane for AI products | | [Agentlas OS](https://github.com/agentlas-ai/Agentlas-OS) | ![][agentlas-stars] | Apache-2.0 local-first agent OS for portable agent and team packages, cross-host orchestration, MCP/A2A, and verification gates | | [Composio](https://github.com/ComposioHQ/composio) | ![](https://img.shields.io/github/stars/ComposioHQ/composio) | 100+ integrations for AI agents via function calling, MCP compatible | | [PocketFlow](https://github.com/The-Pocket/PocketFlow) | ![](https://img.shields.io/github/stars/The-Pocket/PocketFlow) | Minimalist 100-line LLM framework for agents, workflows, and RAG | | [CAMEL](https://github.com/camel-ai/camel) | ![](https://img.shields.io/github/stars/camel-ai/camel) | Multi-agent framework for communicative agents research | | [Strands Agents SDK](https://github.com/strands-agents/harness-sdk) | ![](https://img.shields.io/github/stars/strands-agents/harness-sdk) | AWS-backed model-driven agent SDK with MCP and multi-provider support | | [Summoner](https://github.com/Summoner-Network/summoner-agents) | ![](https://img.shields.io/github/stars/Summoner-Network/summoner-agents) | Agent-to-agent networking for server-decoupled agents over long-lived TCP sessions (Python/Rust), 50+ runnable templates | | [KodeAgent](https://github.com/barun-saha/kodeagent) | ![](https://img.shields.io/github/stars/barun-saha/kodeagent) | The Minimal Agent Engine to build ReAct & CodeAct agents, with support for code sandbox and observability | | [Hivemoot Colony](https://github.com/hivemoot/colony) | ![](https://img.shields.io/github/stars/hivemoot/colony) | Self-governing multi-agent platform; agents propose, vote, peer-review, and ship software via democratic consensus | | [OIXA Protocol](https://github.com/ivoshemi-sys/oixa-protocol) | ![](https://img.shields.io/github/stars/ivoshemi-sys/oixa-protocol) | Agent-to-agent economic marketplace protocol on Base with on-chain escrow and A2A integrations | | [smolagents](https://github.com/huggingface/smolagents) | ![](https://img.shields.io/github/stars/huggingface/smolagents) | Code-first agent library by Hugging Face, model-agnostic with MCP and sandbox support | | [LlamaIndex](https://github.com/run-llama/llama_index) | ![](https://img.shields.io/github/stars/run-llama/llama_index) | Data framework for LLM apps with RAG, agents, and 300+ integrations | | [Mastra](https://github.com/mastra-ai/mastra) | ![](https://img.shields.io/github/stars/mastra-ai/mastra) | TypeScript AI framework for agents, workflows, MCP servers, and evals | | [Hivekeep](https://github.com/MarlBurroW/hivekeep) | ![](https://img.shields.io/github/stars/MarlBurroW/hivekeep) | Self-hosted platform to run a team of specialized AI agents with persistent memory, a web UI, and Telegram/Slack/Discord/Matrix channels, in a single Bun and SQLite container | | [Orkas](https://github.com/Orkas-AI/Orkas) | ![](https://img.shields.io/github/stars/Orkas-AI/Orkas) | Local-first workspace coordinating specialist AI agents across projects | | [Better Agent](https://github.com/ofekron/better-agent) | ![](https://img.shields.io/github/stars/ofekron/better-agent) | Source-available workspace for running and supervising Claude, Codex, and Gemini coding-agent sessions | | [fractal](https://github.com/plasma-ai/fractal) | ![](https://img.shields.io/github/stars/plasma-ai/fractal) | Hierarchical coding-agent runtime with bounded autonomous loops, recursive delegation, isolated Git worktrees, persistent SQLite state, and live operator controls | | [YYLO](https://github.com/yylo-dev/yylo) | ![](https://img.shields.io/github/stars/yylo-dev/yylo) | Command-line orchestrator for coding agents with typed task, validation, merge, and release-readiness boundaries, a dedicated branch/worktree, and risk-based merge review | | [SandBase Harness](https://github.com/sandbaseai/sandbase-harness) | ![](https://img.shields.io/github/stars/sandbaseai/sandbase-harness) | Local-first, self-hosted TypeScript agent runtime and MCP bridge with sandboxed sessions and audit/replay | | [Tale](https://github.com/tale-project/tale) | ![](https://img.shields.io/github/stars/tale-project/tale) | Self-hosted workspace for people and AI agents, with shared project tasks, manager delegation, persistent sandbox workspaces, and human review of results | [agentlas-stars]: https://img.shields.io/github/stars/agentlas-ai/Agentlas-OS --- ## 🚀 Specialized Agents Agents designed for specific tasks or industries. ### 💻 Coding Agents | Name | Stars | Description | | ------------------------------------------------------------ | ------------------------------------------------------------------ | ----------------------------------------------------------------------- | | [SWE-agent](https://github.com/SWE-agent/SWE-agent) | ![](https://img.shields.io/github/stars/SWE-agent/SWE-agent) | AI agent for software engineering tasks | | [GPT Pilot](https://github.com/Pythagora-io/gpt-pilot) | ![](https://img.shields.io/github/stars/Pythagora-io/gpt-pilot) | Assists in writing and debugging code | | [OpenHands](https://github.com/OpenHands/OpenHands) | ![](https://img.shields.io/github/stars/OpenHands/OpenHands) | Open-source AI software development agents (formerly OpenDevin) | | [Devika](https://github.com/stitionai/devika) | ![](https://img.shields.io/github/stars/stitionai/devika) | Agentic AI Software Engineer that writes code from natural instructions | | [Aider](https://github.com/Aider-AI/aider) | ![](https://img.shields.io/github/stars/Aider-AI/aider) | AI pair programming in terminal | | [Plandex](https://github.com/plandex-ai/plandex) | ![](https://img.shields.io/github/stars/plandex-ai/plandex) | AI coding engine for complex projects | | [TaskWeaver](https://github.com/microsoft/TaskWeaver) | ![](https://img.shields.io/github/stars/microsoft/TaskWeaver) | Code-first agent framework for analytical tasks | | [Gemini CLI](https://github.com/google-gemini/gemini-cli) | ![](https://img.shields.io/github/stars/google-gemini/gemini-cli) | Open-source AI agent bringing Gemini to the terminal with MCP support | | [AgenticSeek](https://github.com/Fosowl/agenticSeek) | ![](https://img.shields.io/github/stars/Fosowl/agenticSeek) | Fully local autonomous agent that browses web and codes without APIs | | [Cline](https://github.com/cline/cline) | ![](https://img.shields.io/github/stars/cline/cline) | Autonomous coding agent in VS Code with MCP, browser use, and terminal | | [Goose](https://github.com/aaif-goose/goose) | ![](https://img.shields.io/github/stars/aaif-goose/goose) | Open-source extensible AI agent by Block for engineering tasks | | [bolt.diy](https://github.com/stackblitz-labs/bolt.diy) | ![](https://img.shields.io/github/stars/stackblitz-labs/bolt.diy) | AI-powered full-stack web development in the browser with 19+ LLMs | | [Atomic Agent](https://github.com/AtomicBot-ai/atomic-agent) | ![](https://img.shields.io/github/stars/AtomicBot-ai/atomic-agent) | Local-first CLI and TUI coding agent, open-weight models, 56 tools, MCP | | [Orbi](https://github.com/orbi-build/orbi) | ![](https://img.shields.io/github/stars/orbi-build/orbi) | Takes a labeled GitHub issue to a reviewed PR and a tagged release | ### 🔬 Research Agents | Name | Stars | Description | | --------------------------------------------------------------- | ------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------- | | [GPT Researcher](https://github.com/assafelovic/gpt-researcher) | ![](https://img.shields.io/github/stars/assafelovic/gpt-researcher) | Autonomous agent for comprehensive research | | [Dr. Claw](https://github.com/OpenLAIR/dr-claw) | ![](https://img.shields.io/github/stars/OpenLAIR/dr-claw) | Local research workspace with survey, ideation, experiment, publication, and promotion stages | | [Storm](https://github.com/stanford-oval/storm) | ![](https://img.shields.io/github/stars/stanford-oval/storm) | Multi-agent system for collaborative reasoning | | [DeerFlow](https://github.com/bytedance/deer-flow) | ![](https://img.shields.io/github/stars/bytedance/deer-flow) | Framework for deep research with web search and Python execution | | [Agon](https://github.com/AutoResearch-Factory/Agon) | ![](https://img.shields.io/github/stars/AutoResearch-Factory/Agon) | Prompt Economy orchestrator: reusable scientist/coder/auditor loops instead of per-task prompts, 18 roles, 10+ disciplines | | [AutoNumerics](https://github.com/Daviddjddu/Autonumerics) | ![](https://img.shields.io/github/stars/Daviddjddu/Autonumerics) | Writes, debugs, and validates classical PDE numerical solvers from plain-language problem descriptions | | [Caesar](https://github.com/jasonzliang/caesar-agent) | ![](https://img.shields.io/github/stars/jasonzliang/caesar-agent) | Builds a knowledge graph while exploring the web, then refines drafts via adversarial synthesis | | [P2PCLAW](https://github.com/Agnuxo1/OpenCLAW-P2P) | ![](https://img.shields.io/github/stars/Agnuxo1/OpenCLAW-P2P) | Decentralized P2P agent swarm for open scientific research | | [CAJAL](https://github.com/Agnuxo1/CAJAL) | ![](https://img.shields.io/github/stars/Agnuxo1/CAJAL) | Local scientific paper generation agent with IMRaD structure and citations | ### 🎨 Creative Agents | Name | Stars | Description | | -------------------------------------------------------------- | --------------------------------------------------------------------- | ---------------------------------------------------------------------------------- | | [ShortGPT](https://github.com/RayVentura/ShortGPT) | ![](https://img.shields.io/github/stars/RayVentura/ShortGPT) | Short-form video generation agent | | [AI-town](https://github.com/a16z-infra/ai-town) | ![](https://img.shields.io/github/stars/a16z-infra/ai-town) | Virtual world simulation with AI agents | | [BulkPublish](https://github.com/azeemkafridi/bulkpublish-api) | ![](https://img.shields.io/github/stars/azeemkafridi/bulkpublish-api) | API and agent skills for drafting, scheduling, and publishing social media content | ### 🌐 Web & Computer Use Agents | Name | Stars | Description | | --------------------------------------------------------------- | -------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- | | [Browser Use](https://github.com/browser-use/browser-use) | ![](https://img.shields.io/github/stars/browser-use/browser-use) | Make websites accessible for AI agents, automate tasks with ease | | [NanoBrowser](https://github.com/nanobrowser/nanobrowser) | ![](https://img.shields.io/github/stars/nanobrowser/nanobrowser) | TypeScript-based AI browsing agent | | [Firecrawl](https://github.com/firecrawl/firecrawl) | ![](https://img.shields.io/github/stars/firecrawl/firecrawl) | Turn websites into LLM-ready markdown or structured data | | [Crawl4AI](https://github.com/unclecode/crawl4ai) | ![](https://img.shields.io/github/stars/unclecode/crawl4ai) | Open-source LLM-friendly web crawler and scraper | | [Stagehand](https://github.com/browserbase/stagehand) | ![](https://img.shields.io/github/stars/browserbase/stagehand) | AI browser automation framework with natural language and code | | [Xquik](https://github.com/Xquik-dev/x-twitter-scraper) | ![](https://img.shields.io/github/stars/Xquik-dev/x-twitter-scraper) | X/Twitter data and action API (REST, MCP, webhooks) that agents call for search, monitoring, and posting | | [Skyvern](https://github.com/Skyvern-AI/skyvern) | ![](https://img.shields.io/github/stars/Skyvern-AI/skyvern) | Browser automation agent using LLMs and computer vision to complete web workflows | | [Playwright MCP](https://github.com/microsoft/playwright-mcp) | ![](https://img.shields.io/github/stars/microsoft/playwright-mcp) | MCP server exposing Playwright browser automation to AI agents | | [Agent S](https://github.com/simular-ai/Agent-S) | ![](https://img.shields.io/github/stars/simular-ai/Agent-S) | Open framework for computer-use agents that operate desktop GUIs like a human | | [UI-TARS Desktop](https://github.com/bytedance/UI-TARS-desktop) | ![](https://img.shields.io/github/stars/bytedance/UI-TARS-desktop) | GUI agent by ByteDance that controls desktop and browser via natural language, built on the UI-TARS vision model | | [agent-qa](https://github.com/vostride/agent-qa) | ![](https://img.shields.io/github/stars/vostride/agent-qa) | Self-improving QA agent for natural-language web and mobile tests | ### 🗣️ Programming Language Agents Agents and frameworks specialized for specific programming languages. | Name | Language | Stars | Description | | ------------------------------------------------------------------------ | ---------- | ------------------------------------------------------------------------ | ---------------------------------------------- | | [TypeChat](https://github.com/microsoft/TypeChat) | TypeScript | ![](https://img.shields.io/github/stars/microsoft/TypeChat) | Type-safe LLM outputs using TypeScript types | | [LangChain.js](https://github.com/langchain-ai/langchainjs) | JavaScript | ![](https://img.shields.io/github/stars/langchain-ai/langchainjs) | JS version of LangChain | | [Semantic Kernel](https://github.com/microsoft/semantic-kernel) | C#/.NET | ![](https://img.shields.io/github/stars/microsoft/semantic-kernel) | Integrate LLMs into .NET apps | | [LangChain4j](https://github.com/langchain4j/langchain4j) | Java | ![](https://img.shields.io/github/stars/langchain4j/langchain4j) | Java implementation of LangChain | | [Haystack](https://github.com/deepset-ai/haystack) | Python | ![](https://img.shields.io/github/stars/deepset-ai/haystack) | Search and question answering agents | | [LlamaIndex.js](https://github.com/run-llama/LlamaIndexTS) | TypeScript | ![](https://img.shields.io/github/stars/run-llama/LlamaIndexTS) | JS version of LlamaIndex | | [LangChain.rb](https://github.com/patterns-ai-core/langchainrb) | Ruby | ![](https://img.shields.io/github/stars/patterns-ai-core/langchainrb) | Ruby implementation of LangChain | | [LangChainGo](https://github.com/tmc/langchaingo) | Go | ![](https://img.shields.io/github/stars/tmc/langchaingo) | Go implementation for LLM orchestration | | [OpenAI Agents (Python)](https://github.com/openai/openai-agents-python) | Python | ![](https://img.shields.io/github/stars/openai/openai-agents-python) | Lightweight, provider-agnostic agent framework | | [Swarms-rs](https://github.com/The-Swarm-Corporation/swarms-rs) | Rust | ![](https://img.shields.io/github/stars/The-Swarm-Corporation/swarms-rs) | Swarm-based agent orchestration in Rust | | [AnythingLLM](https://github.com/Mintplex-Labs/anything-llm) | JavaScript | ![](https://img.shields.io/github/stars/Mintplex-Labs/anything-llm) | All-in-one AI agent builder with RAG and UI | ### 🎙️ Voice Agents Frameworks for building real-time voice and conversational AI agents. | Name | Stars | Description | | --------------------------------------------------------------- | -------------------------------------------------------------------- | --------------------------------------------------------------------------------------- | | [Pipecat](https://github.com/pipecat-ai/pipecat) | ![](https://img.shields.io/github/stars/pipecat-ai/pipecat) | Open-source framework for building real-time voice and multimodal conversational agents | | [LiveKit Agents](https://github.com/livekit/agents) | ![](https://img.shields.io/github/stars/livekit/agents) | Framework for real-time voice AI agents with WebRTC transport, built on LiveKit | | [TEN Framework](https://github.com/TEN-framework/ten-framework) | ![](https://img.shields.io/github/stars/TEN-framework/ten-framework) | Open-source framework for real-time conversational voice agents with multimodal support | --- ## ⚙️ Agent Operations Tools and systems for managing AI agents. ### 🧠 Memory | Name | Stars | Description | | ---------------------------------------------------------------------- | ----------------------------------------------------------------------- | --------------------------------------------------------------------------------- | | [Letta (formerly MemGPT)](https://github.com/letta-ai/letta) | ![](https://img.shields.io/github/stars/letta-ai/letta) | Dynamic, adaptive agent memory system | | [Mem0](https://github.com/mem0ai/mem0) | ![](https://img.shields.io/github/stars/mem0ai/mem0) | Universal memory layer for AI agents | | [Tree Ring Memory](https://github.com/TerminallyLazy/Tree-Ring-Memory) | ![](https://img.shields.io/github/stars/TerminallyLazy/Tree-Ring-Memory) | Local-first CLI/TUI for agent memory recall, forgetting, audit, and consolidation | | [ChromaDB](https://github.com/chroma-core/chroma) | ![](https://img.shields.io/github/stars/chroma-core/chroma) | Vector DB for memory/context | | [Weaviate](https://github.com/weaviate/weaviate) | ![](https://img.shields.io/github/stars/weaviate/weaviate) | Scalable vector DB for semantic memory | | [Portable Handoff](https://github.com/legoambarish/portable-handoff) | ![](https://img.shields.io/github/stars/legoambarish/portable-handoff) | Local-first CLI for handing off coding-agent session context between tools | | [Mnemoverse](https://github.com/mnemoverse/mcp-memory-server) | ![](https://img.shields.io/github/stars/mnemoverse/mcp-memory-server) | MIT MCP memory server; a hosted engine re-ranks recall from reported outcomes | | [Fidelis Memory](https://github.com/hermes-labs-ai/fidelis) | ![](https://img.shields.io/github/stars/hermes-labs-ai/fidelis) | Local-first MCP memory: local vector recall, optional keyword+vector hybrid mode | | [Screenpipe](https://github.com/screenpipe/screenpipe) | ![](https://img.shields.io/github/stars/screenpipe/screenpipe) | Source-available screen/audio history for agents via MCP and a local API | | [Busabase](https://github.com/busabase/busabase) | ![](https://img.shields.io/github/stars/busabase/busabase) | Open-source agent workspace with auditable, permission-aware ChangeRequests | ### 📊 Evaluation | Name | Stars | Description | | --------------------------------------------------------------- | ----------------------------------------------------------------- | ------------------------------------------------------------------------------------- | | [AgentBench](https://github.com/THUDM/AgentBench) | ![](https://img.shields.io/github/stars/THUDM/AgentBench) | Multi-environment testing for agents | | [LangTrace](https://github.com/Scale3-Labs/langtrace) | ![](https://img.shields.io/github/stars/Scale3-Labs/langtrace) | Monitoring and trace visualization | | [agenttrace](https://github.com/luoyuctl/agenttrace) | ![](https://img.shields.io/github/stars/luoyuctl/agenttrace) | Local TUI and reports for AI coding agent session cost, latency, failures, and health | | [ax](https://github.com/Necmttn/ax) | ![](https://img.shields.io/github/stars/Necmttn/ax) | Local-first evidence graph for coding-agent sessions, tool calls, skills, and cost | | [Agent Evaluation](https://github.com/awslabs/agent-evaluation) | ![](https://img.shields.io/github/stars/awslabs/agent-evaluation) | Benchmarking agent capabilities | | [Simple Evals](https://github.com/openai/simple-evals) | ![](https://img.shields.io/github/stars/openai/simple-evals) | OpenAI's lightweight LLM evaluation library | ### 📈 Observability Tracing, monitoring, and debugging tools for agents in production. | Name | Stars | Description | | ---------------------------------------------------------------- | --------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- | | [Langfuse](https://github.com/langfuse/langfuse) | ![](https://img.shields.io/github/stars/langfuse/langfuse) | Open-source LLM engineering platform for tracing, prompt management, and evaluations | | [Arize Phoenix](https://github.com/Arize-ai/phoenix) | ![](https://img.shields.io/github/stars/Arize-ai/phoenix) | Open-source AI observability with OpenTelemetry tracing, evals, and agent debugging | | [Helicone](https://github.com/Helicone/helicone) | ![](https://img.shields.io/github/stars/Helicone/helicone) | Open-source LLM observability with one-line integration for cost and usage tracking | | [OpenLLMetry](https://github.com/traceloop/openllmetry) | ![](https://img.shields.io/github/stars/traceloop/openllmetry) | OpenTelemetry-based instrumentation for LLM and agent frameworks | | [Laminar](https://github.com/lmnr-ai/lmnr) | ![](https://img.shields.io/github/stars/lmnr-ai/lmnr) | Open-source platform for tracing and evaluating AI agents | | [Noveum Trace](https://github.com/Noveum/noveum-trace) | ![](https://img.shields.io/github/stars/Noveum/noveum-trace) | Python SDK for tracing LLM calls and agent workflows in the hosted Noveum platform | | [OrcaReplay](https://github.com/Continuum-AI-Corp/OrcaReplay) | ![](https://img.shields.io/github/stars/Continuum-AI-Corp/OrcaReplay) | Records a coding-agent run below the harness and replays it offline byte-for-byte | | [OpenClaw Monitor](https://github.com/flik2002/openclaw-monitor) | ![](https://img.shields.io/github/stars/flik2002/openclaw-monitor) | Open-source monitoring dashboard for OpenClaw AI agents — token usage, session tracking, 7-day trends | | [Bifrost](https://github.com/maximhq/bifrost) | ![](https://img.shields.io/github/stars/maximhq/bifrost) | OpenAI-compatible LLM gateway with multi-provider routing, failover, and tracing | ### 🚀 Deployment | Name | Stars | Description | | --------------------------------------------------- | ---------------------------------------------------------------- | -------------------------------------------- | | [Daytona](https://github.com/daytonaio/daytona) | ![](https://img.shields.io/github/stars/daytonaio/daytona) | Elastic infrastructure for AI-generated code | | [E2B](https://github.com/e2b-dev/E2B) | ![](https://img.shields.io/github/stars/e2b-dev/E2B) | Secure sandboxed environments for agents | | [OctoAI](https://github.com/octoai/octoAI) | ![](https://img.shields.io/github/stars/octoai/octoAI) | Scalable infrastructure for agent deployment | | [Modal](https://github.com/modal-labs/modal-client) | ![](https://img.shields.io/github/stars/modal-labs/modal-client) | Serverless runtime for AI workloads | ### 🔒 Security & Governance | Name | Stars | Description | | --------------------------------------------------------------------------------- | --------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ | | [Agent Governance Toolkit](https://github.com/microsoft/agent-governance-toolkit) | ![](https://img.shields.io/github/stars/microsoft/agent-governance-toolkit) | Policy enforcement, zero-trust identity, and execution sandboxing for autonomous AI agents | | [Garak](https://github.com/NVIDIA/garak) | ![](https://img.shields.io/github/stars/NVIDIA/garak) | LLM vulnerability scanner - probes for prompt injection, data leakage, and hallucination | | [Presidio](https://github.com/data-privacy-stack/presidio) | ![](https://img.shields.io/github/stars/data-privacy-stack/presidio) | PII detection, redaction, and anonymization across text, images, and structured data | | [Guardrails AI](https://github.com/guardrails-ai/guardrails) | ![](https://img.shields.io/github/stars/guardrails-ai/guardrails) | Output validation and guardrails for LLM responses | | [NeMo Guardrails](https://github.com/NVIDIA-NeMo/Guardrails) | ![](https://img.shields.io/github/stars/NVIDIA-NeMo/Guardrails) | Programmable guardrails for LLM-based conversational systems | | [LLM Guard](https://github.com/protectai/llm-guard) | ![](https://img.shields.io/github/stars/protectai/llm-guard) | Security toolkit for scanning and sanitizing LLM prompts and outputs | | [Polaxis](https://github.com/nishant6118/Polaxis-SDK-MCP) | ![](https://img.shields.io/github/stars/nishant6118/Polaxis-SDK-MCP) | Pre-execution runtime firewall for AI agents - 7-layer threat detection and spend controls | | [sofagent](https://github.com/KongFangXun/sofagent) | ![](https://img.shields.io/github/stars/KongFangXun/sofagent) | Commit-time audit harness for coding agents - git-diff rules, HMAC audit trail, rollback | | [hermes-jailbench](https://github.com/hermes-labs-ai/hermes-jailbench) | ![](https://img.shields.io/github/stars/hermes-labs-ai/hermes-jailbench) | Deterministic jailbreak regression benchmark for known-pattern attacks | | [LintLang](https://github.com/hermes-labs-ai/lintlang) | ![](https://img.shields.io/github/stars/hermes-labs-ai/lintlang) | Zero-LLM static analysis for agent configs, tool descriptions, and prompts | | [Little Canary](https://github.com/hermes-labs-ai/little-canary) | ![](https://img.shields.io/github/stars/hermes-labs-ai/little-canary) | Sacrificial-canary prompt-injection preflight (block / flag / pass) | ### 🔌 Protocols Open protocols and implementations for agent-to-tool and agent-to-agent interoperability. | Name | Stars | Description | | -------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- | | [Model Context Protocol](https://github.com/modelcontextprotocol/modelcontextprotocol) | ![](https://img.shields.io/github/stars/modelcontextprotocol/modelcontextprotocol) | Anthropic's open protocol standardizing how AI agents connect to tools and data sources | | [MCP Servers](https://github.com/modelcontextprotocol/servers) | ![](https://img.shields.io/github/stars/modelcontextprotocol/servers) | Official collection of reference MCP server implementations | | [A2A](https://github.com/a2aproject/A2A) | ![](https://img.shields.io/github/stars/a2aproject/A2A) | Open protocol started by Google for agent-to-agent communication across frameworks | | [FastMCP](https://github.com/PrefectHQ/fastmcp) | ![](https://img.shields.io/github/stars/PrefectHQ/fastmcp) | Pythonic framework for building MCP servers and clients | --- ## 📚 Research & Benchmarks Key research papers, benchmarks, and surveys on AI agents. ### 📄 Papers | Title | Link | Description | | ----------------------------------------------------------------------- | ----------------------------------------- | --------------------------------------------------------------------------------------------------------------- | | The Rise of LLM-Based Agents | [arXiv](https://arxiv.org/abs/2309.07864) | Comprehensive survey on LLM-based agents | | Tool Learning with Foundation Models | [arXiv](https://arxiv.org/abs/2304.08354) | Tool usage in AI agents | | Multi-Agent Collaboration | [arXiv](https://arxiv.org/abs/2308.08262) | Collaboration in multi-agent systems | | Large Language Model based Multi-Agents | [arXiv](https://arxiv.org/abs/2312.01845) | Survey of progress and challenges | | Agentic AI Systems | [arXiv](https://arxiv.org/abs/2401.08231) | Components and applications of agentic AI | | A Survey on LLM-based Autonomous Agents | [arXiv](https://arxiv.org/abs/2308.11432) | Focus on autonomous LLM agents | | OptimAI: Optimization from Natural Language Using LLM-Powered AI Agents | [arXiv](https://arxiv.org/abs/2504.16918) | Four-agent pipeline with bandit scheduling turns optimization problems into solver code | | Training Agents to Evolve with Their Harness (HAT) | [arXiv](https://arxiv.org/abs/2608.15763) | Harness-aware training for a live-commerce agent, with evaluation on changing skills, tools, prompts, and hooks | | The Agent Loop: A Survey of Control Strategies, Skills, and Harnesses | [SSRN](https://ssrn.com/abstract=7186738) | Control strategies, agentic RL, termination and recovery, skills, and harnesses around the agent loop | ### 📊 Benchmarks | Name | Stars | Description | | --------------------------------------------------------------------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ | | [ToolBench](https://github.com/OpenBMB/ToolBench) | ![](https://img.shields.io/github/stars/OpenBMB/ToolBench) | Benchmark for tool learning | | [SOTOPIA-π](https://github.com/sotopia-lab/sotopia-pi) | ![](https://img.shields.io/github/stars/sotopia-lab/sotopia-pi) | Social intelligence benchmark for multi-agent systems | | [PerspectiveGap](https://github.com/WhymustIhaveaname/PerspectiveGap) | ![](https://img.shields.io/github/stars/WhymustIhaveaname/PerspectiveGap) | Benchmark for writing orchestration prompts in multi-agent systems, 110 scenarios across 10 topologies | | [ClawBench](https://github.com/TIGER-AI-Lab/ClawBench) | ![](https://img.shields.io/github/stars/TIGER-AI-Lab/ClawBench) | Live-web browser-agent benchmark with 283 tasks across 163 real websites | --- ## 🌐 Community Resources Join the conversation and stay updated on AI agent developments. ### 👥 Communities | Name | Link | Description | | ------------------- | ---------------------------------------------------------- | ---------------------------------------------------- | | LangChain Community | [Discord](https://discord.gg/langchain) | Active developer community | | AutoGen Discussions | [GitHub](https://github.com/microsoft/autogen/discussions) | Microsoft AutoGen community forum | | AgentOps Discord | [Join](https://discord.gg/agentops) | Developer space for observability and testing agents | | Letta AI Community | [Discord](https://discord.gg/letta) | Discussions on adaptive memory in AI agents | ### 📰 Newsletters | Name | Link | Description | | --------------------------- | --------------------------------------------------- | --------------------------- | | The Batch (DeepLearning.AI) | [Subscribe](https://www.deeplearning.ai/the-batch/) | Weekly AI industry insights | --- ## 🚀 Contributors A huge thank you to all our [amazing contributors](https://github.com/NipunaRanasinghe/awesome-ai-agents/graphs/contributors)! Your contributions make this project better every day. ⭐ A special shoutout to all our [stargazers](https://github.com/NipunaRanasinghe/awesome-ai-agents/stargazers) for your support! **Star this repository** to stay updated and help grow the community of AI enthusiasts! ## Contributing Your contributions are welcome! Here's how to get started: - Fork the [repository](https://github.com/NipunaRanasinghe/awesome-ai-agents/fork) and clone it locally. - Add your resource to the appropriate section in `README.md`. - Ensure the resource is: - Relevant to AI agents. - Actively maintained (updated within the last 6 months). - Includes a brief description and link. - Submit a pull request with a clear description of your changes. For more details, see the [CONTRIBUTING.md](CONTRIBUTING.md) guide.