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WiseVision/mcp_server_ros_2

by Various

Advanced MCP Server ROS 2 bridging AI agents straight into robotics

W

MCP

WiseVision/mcp_server_ros_2

Added 1 June 2026

#ai #mcp #mcp-server #mcp-server-ros2 #ros2 #ros2-mcp-server

Overview

A Python-based MCP server that connects AI agents to ROS 2 robotics systems. It enables agents to interact with robotic hardware and software through standardized MCP interfaces. The server handles communication between the AI agent and ROS 2 topics, services, and actions.

Best for

Best for
Developers connecting MCP-compatible AI agents to real ROS 2 robots

Use cases

  • Controlling robot navigation via natural language commands
  • Feeding sensor data from ROS 2 topics into AI decision models
  • Triggering robot actions through MCP tool calls

How to use

Install

npx @modelcontextprotocol/inspector uv --directory /path/to/ros2_mcp run mcp_ros_2_server

Tools exposed

  • ros2_topic_list
  • ros2_topic_subscribe
  • ros2_get_messages
  • ros2_get_message_fields
  • ros2_topic_publish
  • ros2_service_list
  • ros2_service_call
  • ros2_list_actions
  • ros2_send_action_goal
  • ros2_cancel_action_goal
  • ros2_action_request_result
  • ros2_action_subscribe_feedback

Tested with

Claude Desktop, Visual Studio Code Copilot, Warp

Notes

A Python-based MCP server that connects AI agents to ROS 2 robotics systems. It enables agents to interact with robotic hardware and software through standardized MCP interfaces. The server handles communication between the AI agent and ROS 2 topics, services, and actions.

78 stars on GitHub. Last updated 2026-05-08. Licensed MPL-2.0.

Use cases

  • Controlling robot navigation via natural language commands
  • Feeding sensor data from ROS 2 topics into AI decision models
  • Triggering robot actions through MCP tool calls

Pros

  • Uses the MCP standard for seamless integration with compatible agents
  • Python codebase with 78 stars indicating community traction
  • Directly bridges AI agents to ROS 2 without proprietary middleware

Cons

  • Relatively new project with limited adoption (78 stars)
  • Requires proficiency in both ROS 2 and the Model Context Protocol
  • No documented support for ROS 1 or simulation environments

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Uses the MCP standard for seamless integration with compatible agents
  • Python codebase with 78 stars indicating community traction
  • Directly bridges AI agents to ROS 2 without proprietary middleware

Cons

  • Relatively new project with limited adoption (78 stars)
  • Requires proficiency in both ROS 2 and the Model Context Protocol
  • No documented support for ROS 1 or simulation environments
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