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# ROS MCP Server 🧠⇄🤖








<!-- mcp-name: io.github.robotmcp/ros-mcp-server -->
<p align="center">
<img src="https://github.com/robotmcp/ros-mcp-server/blob/main/docs/images/framework.png"/>
</p>
ROS-MCP-Server connects large language models (such as Claude, GPT, and Gemini) to robots, enabling bidirectional communication with no changes to existing robot source code.
### Why ROS-MCP?
- **No robot source code changes** → just add the `rosbridge` node to your existing ROS setup.
- **True two-way communication** → LLMs can both *control* robots and *observe* everything happening on the Robot.
- **Full context** → publish & subscribe to topics, call services & actions, set parameters, read sensor data, and monitor robot state in real time.
- **Deep ROS understanding** → guides the LLM to discover available topics, services, actions, and their types (including custom ones) — enabling it to use them with the right syntax without manual configuration.
- **Works with any MCP client** → built on the open [MCP standard](https://modelcontextprotocol.io/), supporting Claude Code, Codex CLI, Gemini CLI, Claude Desktop, ChatGPT, Cursor, and more.
- **Works across ROS versions** → compatible across ROS 2 (Jazzy, Humble, and others) and ROS 1 distros.
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## 🎥 Examples in Action
<p align="center">
<a href="https://youtu.be/Yy1loJAn9sA">
<img src="https://github.com/robotmcp/ros-mcp-server/blob/main/docs/images/MCP%20Demos%20Slide%20-%207to12s.gif" alt="ROS MCP demos" />
</a>
</p>
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🏭 **Example - AI Agent diagnosis of Industrial Robot End Effector** ([Video](https://youtu.be/EhZNFULz9P4))
- The MCP server connects Claude to a production industrial robot, with only the technician manuals as reference.
- Claude discovers the robot's custom topic and service types and their syntax on its own.
- From a single prompt to test the gripper, it reads the manuals, runs its own tests, finds an anomaly, and reports the root cause.
<p align="center">
<a href="https://youtu.be/EhZNFULz9P4">
<img src="https://github.com/robotmcp/ros-mcp-server/blob/main/docs/images/ROS%20MCP%20Gripper%20vacuum%20test.jpg" width="400" alt="Testing and debugging an industrial robot" />
</a>
</p>
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🤖 **Example - Controlling "Wilson" with natural language** ([video](https://www.traceglarue.com/wilson))
From a single prompt — *"Grab a Coke from the fridge & go to the living room."* — Google Gemini uses the MCP server to navigate and manipulate autonomously. Built on ROS 2 with Nav2 (SLAM) for mapping and navigation, and MoveIt to command the manipulator.
<p align="center">
<a href="https://www.traceglarue.com/wilson">
<img src="https://github.com/robotmcp/ros-mcp-server/blob/main/docs/images/Wilson%20thumbnail.jpg" width="400" alt="Wilson robot controlled with natural language" />
</a>
</p>
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🐕 **Example - Controlling Unitree Go2 in NVIDIA Isaac Sim** ([video](https://www.youtube.com/watch?v=9StFx4lnvmc))
The MCP server connects Claude to a simulated Unitree Go2 quadruped in NVIDIA Isaac Sim, interpreting natural language commands to navigate and control the robot.
<p align="center">
<a href="https://www.youtube.com/watch?v=9StFx4lnvmc">
<img src="https://img.youtube.com/vi/9StFx4lnvmc/maxresdefault.jpg" width="400" alt="Controlling Unitree Go2 in NVIDIA Isaac Sim" />
</a>
</p>
---
## 🛠 Getting Started
Follow the [installation guide](docs/install/installation.md) to get started.
ROS-MCP works with Claude Code, Codex CLI, Gemini CLI, Claude Desktop, ChatGPT, Cursor, or any MCP-compatible client.
<p align="center">
<img src="https://github.com/robotmcp/ros-mcp-server/blob/main/docs/images/MCP_topology.png"/>
</p>
---
## 📚 More Examples & Tutorials
Browse our [examples](examples) to see the server in action.
We welcome community PRs with new examples and integrations!
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## 🤝 Contributing
We love contributions of all kinds:
- Bug fixes and documentation updates
- New features (e.g., Action support, permissions)
- Additional examples and tutorials
Check out the [contributing guidelines](docs/contributing.md) and see issues tagged **good first issue** to get started.
---
## 📜 License
This project is licensed under the [Apache License 2.0](LICENSE).
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