Curated List of 260+ AI Agent Tools with Claude Ecosystem Highlights
A developer has shared a curated list of over 260 AI agent tools on GitHub, with specific attention to tools within the Claude ecosystem. The list is CC0 licensed and includes both Claude-specific tools and those that integrate well with Claude models.
Claude-Specific Tools
- Claude Code - Achieves 80.9% on SWE-bench and supports Agent Teams
- Claude Computer Use - Provides desktop and browser control capabilities
- Claude in Chrome - A browsing agent currently in beta
- Claude Cowork - Desktop automation tool
- MCP (Model Context Protocol) - Described as the "USB-C for AI"
- Anthropic SDK - Official SDK for Claude integration
- Anthropic Cookbook - Documentation and examples for Claude
Tools That Work Well with Claude
- Cline - VS Code extension for Claude
- RooCode - VS Code extension for Claude
- Cursor - Code editor that supports Claude models
- Browser Use - Open-source tool used by Manus
- Major agent frameworks - LangChain, CrewAI, and others
The repository contains 230+ additional tools across categories including voice AI, video generation, CRM agents, self-hosted solutions, frameworks, and benchmarks. The maintainer is open to adding missing tools and the list is actively maintained.
📖 Read the full source: r/ClaudeAI
👀 See Also
Connecting OpenClaw to Qwen2.5 Coder: Feasibility and Considerations
Explore the possibility of connecting OpenClaw to a local Qwen2.5 Coder model with 7 billion parameters to address rate limits with API Gemini 3.
Troubleshooting Email and Google Drive Access for AI Agents
Setting up email and Google Drive access for AI bots on AWS can trigger account blocks. Here's a solution using Gmail and Workspace domains.
KANBAII: A Visual Kanban Board Built with Claude Code for AI-Assisted Development
A developer built KANBAII, a local kanban board tool entirely with Claude Code over two months. It provides visual task management, AI planning, and parallel execution modes for Claude Code workflows.
AVP Protocol Enables LLM Agents to Share KV-Cache Instead of Text for Token Efficiency
AVP (Agent Vector Protocol) allows LLM agents to pass KV-cache directly between them instead of text, reducing token processing by 73-78% and achieving 2-4x speedups across Qwen, Llama, and DeepSeek models. The protocol works with HuggingFace and vLLM connectors and is available as a Python package.