多机器人控制
STDIO多机器人控制的MCP服务器
多机器人控制的MCP服务器
This project creates an MCP (Model Context Protocol) server that allows AI agents to control multiple robots via existing FastAPI robot control servers.
uv pip install -e .
Start the robot control FastAPI servers:
Important Update: The Claude desktop client now automatically runs the MCP server for you
python server.pyThe MCP server allows AI agents to control multiple robots and access their cameras.
All tools accept a port parameter (default: 8000) to specify which robot to control.
drive_forward: Move a robot forwarddrive_backward: Move a robot backwardturn_left: Turn a robot leftturn_right: Turn a robot rightstop: Stop robot movementdrive: Control with precise velocity valuesbeep: Play a sound through a robot's speakerget_camera_image: Get an image from a robot's camerarobot_status: Get robot status informationlist_available_robots: List all available robots and their statusrobot://info/{port}: Get information about a specific robot's capabilities# Get status from robot on port 8000 status_robot1 = await client.robot_status(port=8000) # Get status from robot on port 8001 status_robot2 = await client.robot_status(port=8001) # Make both robots beep with different tones await client.beep(port=8000, frequency=440, duration=1.0) # A4 note on robot 1 await client.beep(port=8001, frequency=523.25, duration=1.0) # C5 note on robot 2 # Get a list of all available robots robots = await client.list_available_robots()
The camera image tools use MCP's native Image class for handling image data. This allows the AI agent to receive the image data in a format that can be properly handled by the client without need for additional conversion.