Connect AI models like Claude & ChatGPT with ROS robots using MCP
The ROS MCP Server connects AI models like Claude and ChatGPT with ROS/ROS2 robots using the Model Context Protocol (MCP). It exposes a bridge between model reasoning and robotic control contexts, enabling model-driven instruction and context sharing within ROS ecosystems.
🛠️ Key Features
ROS and ROS2 MCP server implementation
Supports model-context communication via MCP
Python 3.10+ compatibility
Dev container ready for streamlined onboarding
Open-source under Apache 2.0
🚀 Use Cases
Integrating AI model reasoning with ROS robot control loops
Sharing model context between cloud LLMs and onboard ROS nodes
Enabling dynamic context updates for robotic applications
⚡ Developer Benefits
Clear ROS/ROS2 MCP integration path
Reusable MCP components for model-context exchange
Easy local development with containerized setup
Transparent open-source repository with active maintenance
⚠️ Limitations
As described, focused on ROS/ROS2 environments; may require ROS setup
Performance depends on network and model latency
Documentation in readme excerpt; deeper usage details may be in repo
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, 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.
🤖 Example - Controlling "Wilson" with natural language (video)
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.
🐕 Example - Controlling Unitree Go2 in NVIDIA Isaac Sim (video)
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.
