WiseVision/mcp_server_ros_2
by Various
Advanced MCP Server ROS 2 bridging AI agents straight into robotics
MCP
WiseVision/mcp_server_ros_2
Added 1 June 2026
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_listros2_topic_subscriberos2_get_messagesros2_get_message_fieldsros2_topic_publishros2_service_listros2_service_callros2_list_actionsros2_send_action_goalros2_cancel_action_goalros2_action_request_resultros2_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
Pairs with
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