ROS MCP Server

The ROS MCP Server is a bridge that connects large language models (LLMs) such as Claude, GPT‑4, and Gemini directly to robotic systems built on ROS or ROS 2. By exposing the full set of ROS topics, services, parameters, and custom message types through the Model Context Protocol (MCP), it allows an LLM to understand and control a robot without any modification to the robot’s existing codebase. This solves a common pain point in robotics research and deployment: the need to write custom middleware or adapters for each new robot platform. Instead, developers can simply run a single node and have the LLM interact with the robot in natural language.

For developers, the server offers a powerful two‑way communication channel. An LLM can issue high‑level commands like “pick up the red block” and the server translates that into a series of ROS topic publishes or service calls. At the same time, the LLM can observe live sensor streams, read parameter values, and inspect message definitions in real time. This bidirectional flow enables sophisticated use cases such as autonomous task planning, live debugging of industrial robots, or teaching a robot new skills through conversational instruction. The server supports both ROS 1 and ROS 2, making it a versatile tool across legacy and modern robotic stacks.

Key capabilities are presented in plain language:

• Topic discovery – list every available topic and its type.
• Message introspection – view the full definition of any message, including custom types.
• Publish/subscribe – send commands or stream data on any topic in real time.
• Service invocation – call standard or custom services to trigger robot actions.
• Parameter management – read and modify runtime parameters on the fly.
  Future releases will add ROS Action support and fine‑grained permission controls for secure deployments.

Typical scenarios include:

• Natural‑language robot control – users can dictate tasks to a mobile manipulator or quadruped and watch the LLM translate those commands into precise ROS messages.
• Live debugging – operators can query the state of an industrial arm, inspect custom message types, and invoke diagnostic services—all through conversational prompts.
• Rapid prototyping – researchers can prototype new behaviors by asking the LLM to explore available services and topics, then immediately test them without writing code.
• Educational tools – students can interact with a robot in plain English, learning both ROS concepts and natural‑language programming simultaneously.

By integrating seamlessly with any MCP‑enabled LLM, the ROS MCP Server elevates robotic automation into an interactive AI experience. It removes the barrier of low‑level ROS programming, enabling developers to focus on higher‑level logic and user experience while the server handles the technical plumbing.