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ai-fange/robotarm-mcp-p340

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a mcp server for p340 robot arm

概要

A Model Context Protocol (MCP) server implementation that provides natural language control for ElephantRobotics MyCobot series robotic arms (especially optimized for ultraArmP340). This server enables controlling robotic arms through conversational AI, making robotics accessible to everyone. - 🤖 Support for multiple MyCobot models (ultraArmP340, MyCobot280, MyCobot320) - 🎮 Natural language control via MCP protocol - 🔧 Simulation mode for development without physical hardware - 🛡️ Safety features including emergency stop - 📊 Real-time status monitoring The server provides the following control tools: - - Connect to a robotic arm - Input: model (string): Robot model - Input: port (string): Serial port - Returns: Connection status - - Get current robot status - Returns: Current angles, coordinates, gripper/pump state, movement status - - Move joints to specific angles - Input: angles (array): Target angles for each joint - Input: speed (int): Movement speed - Returns: Movement...

README

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RobotArm MCP P340

English | 中文

Overview

A Model Context Protocol (MCP) server implementation that provides natural language control for ElephantRobotics MyCobot series robotic arms (especially optimized for ultraArmP340). This server enables controlling robotic arms through conversational AI, making robotics accessible to everyone.

Features

  • 🤖 Support for multiple MyCobot models (ultraArmP340, MyCobot280, MyCobot320)
  • 🎮 Natural language control via MCP protocol
  • 🔧 Simulation mode for development without physical hardware
  • 🛡️ Safety features including emergency stop
  • 📊 Real-time status monitoring

Components

Tools

The server provides the following control tools:

Connection Management

  • connect_robot - Connect to a robotic arm
    • Input: model (string): Robot model
    • Input: port (string): Serial port
    • Returns: Connection status

Status Monitoring

  • get_robot_status - Get current robot status
    • Returns: Current angles, coordinates, gripper/pump state, movement status

Movement Control

  • move_to_angles - Move joints to specific angles

    • Input: angles (array): Target angles for each joint
    • Input: speed (int): Movement speed
    • Returns: Movement confirmation
  • move_to_coords - Move to specific coordinates

    • Input: coords (array): Target coordinates
    • Input: speed (int): Movement speed
    • Returns: Movement confirmation

End Effector Control

  • control_gripper - Control gripper open/close
  • control_pump - Control suction pump on/off

System Commands

  • go_zero - Return robot to zero position
  • emergency_stop - Emergency stop all movements

Advanced Motion Control

  • execute_action_sequence - Execute custom action sequences
    • Input: sequence_name (string): Descriptive name for the sequence
    • Input: actions (array): List of actions, each containing:
      • type: Action type (“angles”, “coords”, “gripper”, “pump”, “wait”)
      • angles/coords: Target position (based on type)
      • speed: Movement speed (optional, default 50)
      • duration: Action duration in seconds (optional)
      • gripper_action: “open” or “close” (for gripper type)
      • pump_action: “on” or “off” (for pump type)
      • Input: default_interval (float): Default interval between actions (optional, default 0.5s)
    • Returns: Execution status with completed actions count
    • Note: This tool enables complex behaviors like cat playing, circle drawing, dancing, and custom gestures through action sequences

Resources

GitHub で README 全文を見る

インストール

This server does not publish a one-line install command.

Open the repository installation guide MCP 初心者?mcpskill.org のガイドから始めましょう →

設定

{ "mcpServers": { "mycobot": { "command": "Fill in the python path under the virtual environment folder where robotarm-mcp-p340 is installed", "args": ["-u", "-m", "mycobot_mcp"], "env": { "SIMULATE": "1" } } } } Example: { "mcpServers": { "mycobot": { "command": "D:\\anaconda3\\envs\\test-robotarm\\python.exe", "args": ["-u", "-m", "mycobot_mcp"], "env": { "SIMULATE": "1" } } } }