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    Bracketbot Mcp

    An MCP server to control a bracket bot that runs the example_server.py in the quickstart repo

    3 stars
    Python
    Updated Aug 25, 2025

    Table of Contents

    • Features
    • Prerequisites
    • Setup
    • Usage
    • Available Tools
    • Movement Control
    • Audio Control
    • Camera Access
    • System Information
    • Available Resources
    • Examples
    • Note on Image Handling

    Table of Contents

    • Features
    • Prerequisites
    • Setup
    • Usage
    • Available Tools
    • Movement Control
    • Audio Control
    • Camera Access
    • System Information
    • Available Resources
    • Examples
    • Note on Image Handling

    Documentation

    Multi-Robot Control MCP Agent

    This project creates an MCP (Model Context Protocol) server that allows AI agents to control multiple robots via existing FastAPI robot control servers.

    Features

    • Control multiple robots simultaneously
    • Control robot movement (forward, backward, left, right)
    • Play sounds through the robots' speakers
    • Get robot status information
    • Precise velocity control
    • Access robot camera images
    • Unified API with port specification

    Prerequisites

    • Python 3.10+
    • UV (Python package manager)
    • Multiple running robot control FastAPI servers (as provided in the example)

    Setup

    1. Ensure you have a Python 3.10 environment active

    2. Install dependencies using UV:

    bash
    uv pip install -e .

    Usage

    1. Start the robot control FastAPI servers:

    • First robot on port 8000
    • any other robots on 8001, 8002, etc

    2. Important Update: The Claude desktop client now automatically runs the MCP server for you

    • No need to manually start the server with python server.py
    • The MCP server functionality is integrated directly into the Claude desktop client

    3. The MCP server allows AI agents to control multiple robots and access their cameras.

    Available Tools

    All tools accept a port parameter (default: 8000) to specify which robot to control.

    Movement Control

    • drive_forward: Move a robot forward
    • drive_backward: Move a robot backward
    • turn_left: Turn a robot left
    • turn_right: Turn a robot right
    • stop: Stop robot movement
    • drive: Control with precise velocity values

    Audio Control

    • beep: Play a sound through a robot's speaker

    Camera Access

    • get_camera_image: Get an image from a robot's camera

    System Information

    • robot_status: Get robot status information
    • list_available_robots: List all available robots and their status

    Available Resources

    • robot://info/{port}: Get information about a specific robot's capabilities

    Examples

    python
    # 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()

    Note on Image Handling

    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.

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