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Colab MCP

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# Colab MCP 🔗 > **Stop losing context when you switch between AI coding tools.** A Model Context Protocol (MCP) server that lets Claude Code, Cursor, Codex, and other AI coding assistants share logs and session history with each other. [![PyPI version](https://badge.fury.io/py/colab-mcp.svg)](https://badge.fury.io/py/colab-mcp) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) ## The Problem You're coding with Claude Code. You make progress. Then you switch to Cursor to test something. Now you've lost all your context. You explain everything again. Then you jump to Codex. Explain it all over again. **It's exhausting.** ## The Solution Colab MCP is a shared MCP server that exposes your chat logs, terminal history, and IDE events as **tools** and **resources** across all your AI coding assistants. When you switch tools, your AI already knows what you were working on. No more copy-pasting. No more re-explaining. Just continuous flow. --- ## ✨ Features - 🔄 **Share context across tools** - Claude Code, Cursor, Codex, Gemini - 📜 **Access chat transcripts** from previous sessions - 🔍 **Search across all logs** - find that conversation from last week - 🎯 **Session summaries** - quick overview of what you were working on - 🖥️ **Terminal & IDE event tracking** - see what commands were run - 🚀 **Fast setup** - one command to install across all your tools --- ## 🚀 Quick Start ### 1. Install ```bash pip install colab-mcp ``` ### 2. Configure Your AI Tools Run the interactive installer: ```bash sudo colab-mcp-install ``` The installer will: - 🔍 Detect which AI coding tools you have installed - ✅ Let you choose which ones to configure - ⚙️ Add Colab MCP to their MCP server configs - 📝 Give you instructions to restart each tool ### 3. Restart Your AI Tools Restart Claude Code, Cursor, Codex, or whichever tools you configured. That's it! 🎉 --- ## 📖 Usage Once installed, Colab MCP exposes several tools and resources to your AI assistants: ### Tools - **`list_sessions`** - Get a list of all coding sessions - **`fetch_transcript`** - Retrieve the full transcript of a session - **`summarize_session`** - Get a quick summary of what happened - **`search_logs`** - Search across all logs (chat, MCP, IDE events) - **`codex_status`** - Check recent Codex CLI activity ### Example Prompts Try asking your AI assistant: > "What was I working on in my last session?" > "Search my logs for discussions about authentication" > "Summarize my session from yesterday afternoon" > "What errors did I encounter in the last hour?" --- ## 🛠️ Manual Configuration If you prefer to configure manually, add this to your MCP config: ### Claude Code (`~/.claude/mcp.json`) ```json { "servers": { "colab-mcp": { "command": "colab-mcp", "env": { "CLAUDE_HOME": "/home/yourusername/.claude", "CURSOR_LOGS": "/home/yourusername/.cursor-server/data/logs", "TMPDIR": "/tmp" } } } } ``` ### Cursor (`~/.cursor/mcp.json`) ```json { "mcpServers": { "colab-mcp": { "command": "colab-mcp", "env": { "CLAUDE_HOME": "/home/yourusername/.claude", "CURSOR_LOGS": "/home/yourusername/.cursor-server/data/logs", "TMPDIR": "/tmp" } } } } ``` ### Codex (`~/.codex/config.toml`) ```toml [mcp_servers.colab-mcp] command = "colab-mcp" args = [] env = { CLAUDE_HOME = "/home/yourusername/.claude", CURSOR_LOGS = "/home/yourusername/.cursor-server/data/logs", TMPDIR = "/tmp" } ``` --- ## 🗂️ Architecture ```mermaid graph TB subgraph AI["AI Tools"] Claude[Claude Code] Cursor[Cursor] Codex[Codex] end MCP[Colab MCP Server] subgraph Logs["Log Files"] Chat[Chat History] IDE[IDE Events] Term[Terminal] end Claude --> MCP Cursor --> MCP Codex --> MCP MCP --> Chat MCP --> IDE MCP --> Term style MCP fill:#e8f4f8,stroke:#4a90a4,stroke-width:2px style AI fill:#f9f9f9,stroke:#ccc style Logs fill:#f9f9f9,stroke:#ccc ``` --- ## 🤝 Contributing Contributions are welcome! Check out the [docs/](docs/) folder for more detailed information about how Colab MCP works. --- ## 📝 License MIT License - see [LICENSE](LICENSE) for details. --- ## 🙏 Acknowledgments Built with [FastMCP](https://github.com/jlowin/fastmcp) - the fastest way to build MCP servers in Python. --- **Made with ❤️ by developers tired of losing context**

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