A Python implementation of the Model Context Protocol (MCP) for ROS 2. This server enables AI tooling to connect with ROS 2 nodes, topics, and services using the MCP standard over stdio. Designed to be the easiest ROS 2 MCP server to configure.

Save hours of development time with native AI integration for your ROS 2 projects:

• ⚡ 1-minute setup - World's easiest ROS 2 MCP configuration
• 0️⃣ Zero-friction setup - stdio transport, no brokers, no webserver.
• 🔌 Auto type discovery - a built-in “list interfaces” tool dynamically enumerates available topics and services together with their message/service definitions (fields, types, schema) — so the client always knows exactly what data can be published or called.
• ✨ Nested field support: Handle complex message structures with ease.
• 🤖 AI-powered debugging - Let AI help you troubleshoot ROS 2 issues in real time
• 📊 Smart data analysis - Query your robot's sensor data using natural language
• 🚀 Boost productivity - Control robots, analyze logs, and debug issues through AI chat
• 💡 No ROS 2 expertise required - AI translates your requests into proper ROS 2 commands
• 🐋 Dockerized: Ready-to-use Docker image for quick deployment.
• 🔧 Auto QoS selection: Automatically selects appropriate Quality of Service settings for topics and services, ensuring optimal communication performance without manual configuration.

Perfect for: Robotics developers, researchers, students, and anyone working with ROS 2 who wants to leverage AI for faster development and debugging.

If you find this useful, please ⭐ star the repo — it helps others discover it.

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Feel free to contribute or reach out for support! Write issues, submit PRs, or join our Discord community to connect with other ROS 2 and AI enthusiasts.

• List available topics
• List available services
• Call services
• Subscribe to topics to collect messages
• Publish messages to topics
• Echo messages on topics
• Get fields from message types
• Get messages from WiseVision Data Black Box (InfluxDB alternative to Rosbag2)

Note: To call a service with a custom (non-default) type, source the package that defines it before starting the server.

Follow the installation guide for step-by-step instructions:

• 🧩 Install in Visual Studio Code Copilot
• 🤖 Install in Claude Desktop
• 💻 Install in Warp
• 🐳 Build Docker Image locally

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory /path/to/mcp_server_ros2 run mcp_ros_2_server

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

We built this server to make AI‑assisted ROS 2 development fast and reliable. Internally, we needed a simple way for agents to discover message types, publish/subscribe to topics, and call services—without boilerplate or flaky networking. That led to a few core design goals:

• Handle all ROS 2 message types (including nested fields) so agents can write and test any code
• Integrate topic pub/sub and service calls to validate behavior end‑to‑end
• Work seamlessly with GitHub Copilot in VS Code and other MCP clients
• Use a simple stdio transport to avoid network complexity

After dogfooding it, we open‑sourced the project to help the broader ROS 2 community build faster with AI. It’s now useful not only for development, but also for controlling robots, running QoS experiments, and analyzing live data and robot/swarm state. The project is actively maintained—features and improvements ship regularly based on user feedback. If this project helps you, please star the repo and share your use case!