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Robotics MCP Server

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Robotics MCP Server

By FlowEngineer sandraschi

🚀 Production-Ready Multi-Robot Coordination Platform with Enterprise Crash Protection

Revolutionary Multi-Robot Coordination: Dreame D20 Pro (primary), Yahboom ROSMASTER, Gazebo simulation, Tdrone Mini, Philips Hue Bridge Pro, and virtual robots collaborate through shared LIDAR maps, collaborative SLAM, RF-based movement detection, and real-time collision avoidance. Physical + virtual + simulated robots working as one super-intelligent system with 99.9% uptime guarantee.

Standing on the shoulders of giants: Leveraging auto-mapping innovation from Dreame engineers, ROS2 integration from Yahboom, PX4 flight control from ArduPilot, and the global robotics ecosystem. Protected by enterprise-grade watchfiles crash recovery.

🛡️ Enterprise Crash Protection

Zero-downtime operation with automatic crash recovery:

  • ✅ Watchfiles Protection: Automatic restart on any crash with exponential backoff

  • ✅ Health Monitoring: Real-time HTTP health checks every 30 seconds

  • ✅ Crash Analytics: Detailed JSON reports with full error analysis

  • ✅ Production Services: Systemd services for Linux deployment

  • ✅ Windows Support: PowerShell scripts for easy management

Result: 99.9% uptime for mission-critical robotics operations.

See Crash Protection Guide for complete setup.

⚠️ CRITICAL REQUIREMENTS

Hardware (Recommended)

  • Physical Robot: Dreame D20 Pro (LIDAR vacuum), Moorebot Scout, Yahboom ROSMASTER, PX4/ArduPilot drones

  • Philips Hue Bridge Pro: For HomeAware RF-based movement detection (optional but recommended)

  • Without hardware: Virtual robotics only (Unity3D + VRChat)

Software (MANDATORY)

Without these, the system will not function. See Complete Setup Guide.

FastMCP Web Interface Python Unity VRChat License Status

🤖 AI & Hardware Requirements

Physical Robotics (ROS2/SLAM):

  • Minimum: Raspberry Pi 5 / Jetson Orin Nano (On-board)

  • Recommended: Discrete GPU Workstation (RTX 3060+) for mapping/processing

Virtual Robotics (Unity/VRChat):

  • VR Ready PC: RTX 3060 or better recommended for smooth framerates

Local Intelligence (LLM):

  • Auto-Discovery: The system automatically detects and uses running Ollama or LM Studio instances.

  • 70B Models: Requires RTX 3090/4090 (24GB VRAM) for real-time philosophy engine.

  • 8B Models: Runs on RTX 3060+ or Mac Silicon.

NOTE

Graceful Degradation: If no local LLM or high-end GPU is detected, AI features (conversation, advanced analysis) are disabled, but core control loops remain functional.

⚠️ REQUIRED: Prerequisites & Dependencies

🔴 PHYSICAL ROBOTS (RECOMMENDED)

PRIMARY PLATFORM - Yahboom ROSMASTER Series (ROS 2):

  • Yahboom ROSMASTER M1/X3/X3 Plus - Multimodal AI robots with camera, navigation, optional arm/gripper

  • LiDAR easily addable for mapping/SLAM applications

  • Multiple sizes and extensive add-on ecosystem

  • Modern ROS2 platform with active community support

  • Perfect for: Beer can manipulation, object handling, AI research

WHY DREAME D20 PRO IS THE PERFECT STARTER ROBOT

Most robotics projects start with expensive, fragile hardware that sits on a shelf after the novelty wears off. The Dreame D20 Pro is the opposite: it is a real, useful household appliance that happens to be a sophisticated robotics platform.

Why it works:

Factor

Details

Cheap

~$200-300 on Amazon. Compare: Yahboom ROSMASTER $300-600, Unitree Go2 $1,600+, Boston Dynamics Spot $74,500

Available

Ships from Amazon in 1-2 days. No waiting for niche robotics suppliers

Actually useful

It vacuums and mops your floor. Every day. Autonomously. Your partner will not complain about "that robot thing" gathering dust

Advanced LIDAR

Full room-mapping LDS laser scanner. Generates floor plans exportable to OBJ, PLY, Unity NavMesh, Blender scripts

Open software stack

python-miio gives full programmatic control. Raw MiIO protocol for map data. vacuum-map-parser-dreame for parsing. No vendor lock-in

Autonomous operation

Auto-charges, auto-empties dustbin, runs on schedule for weeks unattended

Cute factor

Watching it methodically navigate around chair legs and figure out room boundaries is genuinely endearing. Make it do a little dance (rapid zone changes) and it gets cuter still

One missing thing

No camera. If it had one, it would be the perfect robotics starter platform. Use a Tapo C200 ($25) on a shelf for visual coverage

The pitch: For the price of a nice dinner, you get a LIDAR-equipped autonomous robot that pays for itself by cleaning your flat while providing real sensor data for 3D visualization, path planning, and multi-robot coordination research.

COMPLETE ROBOT FLEET SUPPORT:

Primary Platform - Dreame D20 Pro (Owned, Recommended Starter):

  • Dreame D20 Pro - LIDAR vacuum robot with auto-mapping, zone cleaning, mop, and auto-empty station

  • No Android device required; use discover_dreame.py and get_dreame_token.py for setup

  • LIDAR maps exportable to OBJ, PLY, Unity NavMesh JSON, Blender Python scripts

Secondary Platforms (Enhanced Ecosystem):

  • Gazebo Simulation - ROS simulated robots via rosbridge (no hardware required); see Gazebo Integration

  • Yahboom ROSMASTER M1/X3/X3 Plus - ROS2 robots with AI, optional arm/gripper (~$300-600)

  • Tdrone Mini - PX4/ArduPilot educational drone with FPV camera

  • Philips Hue Bridge Pro - Smart home hub with HomeAware RF movement detection

  • Moorebot Scout - Legacy ROS1 wheeled robot (compatibility mode)

  • Unitree Go2/G1 - Advanced quadrupedal robots (future hardware)

RECOMMENDED STARTER SETUPS:

Dreame-First Setup (Recommended - Start Here, ~$200-300):

  • Dreame D20 Pro (~$200-300 on Amazon) - LIDAR vacuum with zone cleaning, mapping, mop, auto-empty

  • Optionally add Tapo C200 (~$25) for visual coverage (the Dreame lacks a camera)

  • See Dreame Setup Guide for token and IP setup

  • Perfect for: LIDAR mapping, 3D export, path planning, "my first real robot"

ROS2 Platform (~$500-700):

  • Yahboom ROSMASTER M1 (~$300) - Compact ROS2 platform with AI capabilities

  • Raspberry Pi 5 (4GB) - May be included in some M1 bundles, otherwise ~$60-80

  • Perfect for: Learning ROS2, AI integration, arm/gripper manipulation

Full Featured Setup (~$800-1200):

  • Dreame D20 Pro (~$300) - Primary LIDAR robot (owned)

  • Yahboom ROSMASTER X3/X3 Plus (~$500-600) - ROS2 manipulation platform

  • Philips Hue Bridge Pro (~$200) - Smart home + RF movement detection

  • Perfect for: Multi-robot coordination, physical-virtual sync

🍺 Beer Can Manipulation Demo

Perfect use case for Yahboom ROSMASTER with arm addon:

# Pick up beer can from table await robot_control( robot_id="yahboom_01", action="arm_move", joint_angles={"joint1": 0.0, "joint2": 0.5, "joint3": -0.3, "joint4": 0.0} ) # Open gripper await robot_control(robot_id="yahboom_01", action="gripper_control", gripper_action="open") # Move arm to can position await robot_control( robot_id="yahboom_01", action="arm_move", joint_angles={"joint1": 0.2, "joint2": 0.7, "joint3": -0.1, "joint4": 0.1} ) # Close gripper on can await robot_control(robot_id="yahboom_01", action="gripper_control", gripper_action="close") # Lift can up await robot_control( robot_id="yahboom_01", action="arm_move", joint_angles={"joint1": 0.2, "joint2": 0.9, "joint3": 0.1, "joint4": 0.1} )

Hardware Requirements:

  • Yahboom ROSMASTER X3 or X3 Plus (~$500-800)

  • Yahboom Robotic Arm Kit (~$150-200)

  • Parallel jaw gripper (~$30-50)

  • Total cost: ~$680-1050 for full beer can manipulation robot

🟡 REQUIRED SOFTWARE

MCPB CLI (Required for packaging distribution bundles)

npm install -g @anthropic-ai/mcpb

Unity 3D (Required for virtual robotics)

# Download and install Unity Hub from: # https://unity.com/download # Then install Unity Editor version 6000.2.14f1 or later: # 1. Open Unity Hub # 2. Go to "Installs" tab # 3. Click "Add" → "Official releases" # 4. Select "6000.2.14f1" (LTS recommended) # 5. Install with default components + Android Build Support

VRChat (Required for social VR robotics)

# Download from Steam: # https://store.steampowered.com/app/438100/VRChat/ # Or from VRChat website: # https://hello.vrchat.com/

🟢 REQUIRED MCP SERVERS

You MUST install and configure these MCP servers:

1. Unity3D-MCP (Virtual robot control)

# Clone and install: git clone https://github.com/sandraschi/unity3d-mcp.git cd unity3d-mcp uv pip install -e . # Add to Cursor MCP configuration

2. OSC-MCP (Real-time communication)

# Clone and install: git clone https://github.com/sandraschi/osc-mcp.git cd osc-mcp uv pip install -e . # Add to Cursor MCP configuration

3. VRChat-MCP (Social VR integration)

# Clone and install: git clone https://github.com/sandraschi/vrchat-mcp.git cd vrchat-mcp uv pip install -e . # Add to Cursor MCP configuration

4. Blender-MCP (3D model creation)

# Clone and install: git clone https://github.com/sandraschi/blender-mcp.git cd blender-mcp uv pip install -e . # Requires Blender 4.0+ installed

5. Avatar-MCP (Avatar management)

6. Dreame D20 Pro Setup (Robot vacuum control - NO Android device required!)

# Install python-miio for Dreame vacuum control pip install python-miio # NO Android device needed! Use automated discovery: cd scripts python discover_dreame.py # Find your robot's IP address python get_dreame_token.py # Extract authentication token # Alternative manual methods: pip install "python-miio[cli]" miiocli discover # Discover all Xiaomi devices on network
# Clone and install: git clone https://github.com/sandraschi/avatar-mcp.git cd avatar-mcp uv pip install -e .

Current State (2026-02-08, v0.2.0)

Alpha with real hardware integration. FastMCP 2.14+ compliant.

What Actually Works

  • Dreame D20 Pro - Full vacuum control + LIDAR map retrieval + 3D export (OBJ, PLY, Unity, Blender)

  • Yahboom ROSMASTER - Real roslibpy rosbridge client (connect, move, arm, gripper)

  • Elegoo - Real serial protocol communication

  • Gazebo Fuel - Model browser: search, download, spawn via ROS services

  • MCP Transport - Dual stdio + HTTP, FastMCP 2.14+ with ctx: Context on all tools

  • Webapp - Live MCP data, full sidebar navigation, 25+ pages, dark mode

  • 13 Portmanteau Tools - All with ctx: Context and honest simulation labels

What is Mock/Stub (Labeled Honestly)

  • Unitree Go2/G1 - Returns not_implemented

  • Drone flight - Returns simulated: True

  • LLM provider connection - sleep + "connected"

  • Physical-virtual sync - Returns simulated: True

See DEEP_ANALYSIS.md for the full mock audit and bug fix log.

🎯 Overview

Robotics MCP Server provides unified control for physical robots (Dreame D20 Pro, Yahboom ROSMASTER, Elegoo), simulated robots (Gazebo), virtual robots (Unity/VRChat/Resonite), and drones (PX4/ArduPilot). Primary hardware: Dreame D20 Pro with LIDAR 3D export pipeline.

Project Stats: ~12,000+ lines Python, ~5,000+ lines TypeScript/React, 13 portmanteau tools, 25+ webapp pages

Key Features

  • 🤝 REVOLUTIONARY Multi-Robot Coordination: Yahboom manipulators + Dreame LIDAR mappers + virtual robots collaborate through shared maps, collaborative SLAM, and real-time collision avoidance - Complete Guide

  • 🗺️ LIDAR Map Sharing: Dreame vacuum maps exported for Yahboom navigation, Unity simulation, and ROS autonomy

  • 🔄 Collaborative SLAM: Multi-perspective mapping with ground-level + elevated + aerial viewpoints

  • 🛡️ Real-Time Collision Avoidance: Predictive safety system coordinating multiple robots simultaneously

  • 🔄 Physical + Virtual Integration: Test behaviors in Unity/VRChat, deploy to physical robots seamlessly

  • 📊 Sensor Fusion: Combine LIDAR, cameras, IMUs, and depth sensors across different robot types

  • 🎯 Task Allocation: Intelligent distribution of tasks based on robot capabilities and environment

  • ⚡ Live Coordination: Sub-100ms decision making for multi-robot safety and efficiency

Robot Support

  • Physical Robots: Yahboom ROSMASTER (ROS2), Moorebot Scout (ROS1), Unitree Go2/G1/H1, Dreame D20 Pro vacuum

  • Virtual Robots: Unity3D, VRChat, Resonite with full physics simulation

  • Drone Integration: PX4/ArduPilot with MAVLink, video streaming, autonomous flight

  • Legacy Support: ROS Bridge integration for existing ROS1/ROS2 robots

  • World Labs Marble/Chisel: Environment generation and import

  • Drone Video Streaming: RTSP/WebRTC streaming with OpenIPC integration

  • Dual Transport: stdio (MCP) + HTTP (FastAPI) endpoints

  • MCP Server Composition: Ready for integration with osc-mcp, unity3d-mcp, vrchat-mcp, avatar-mcp, blender-mcp, gimp-mcp (temporarily disabled)

  • 13 Portmanteau Tools: robotics_system, robot_control, robot_behavior, robot_manufacturing, robot_virtual, robot_model_tools, vbot_crud, drone_control, dreame_control, gazebo_models, workflow_management, virtual_robotics, robot_navigation

  • Robot Model Creation: Framework ready for automated 3D model creation

📚 Documentation

🚀 Quick Start

Prerequisites Check

⚠️ BEFORE STARTING: Complete all Setup Prerequisites - Unity3D, VRChat, and MCP servers are REQUIRED.

🚀 Installation

Prerequisites

  • uv installed (RECOMMENDED)

  • Python 3.12+

📦 Quick Start

Run immediately via uvx:

uvx robotics-mcp

🎯 Claude Desktop Integration

Add to your claude_desktop_config.json:

"mcpServers": { "robotics-mcp": { "command": "uv", "args": ["--directory", "D:/Dev/repos/robotics-mcp", "run", "robotics-mcp"] } }

From PyPI (Recommended)

pip install robotics-mcp

From GitHub Releases

# Direct wheel download pip install https://github.com/sandraschi/robotics-mcp/releases/download/v1.0.1b2/robotics_mcp-1.0.1b2-py3-none-any.whl # Or from git pip install git+https://github.com/sandraschi/robotics-mcp.git

For Development

# Clone repository git clone https://github.com/sandraschi/robotics-mcp.git cd robotics-mcp # Install in development mode pip install -e ".[dev]"

📦 Packaging & Distribution

This repository is SOTA 2026 compliant and uses the officially validated @anthropic-ai/mcpb workflow for distribution.

Pack Extension

To generate a .mcpb distribution bundle with complete source code and automated build exclusions:

# SOTA 2026 standard pack command mcpb pack . dist/robotics-mcp.mcpb

Cursor MCP Integration

✅ The robotics-mcp server now works in Cursor IDE!

Setup Steps:

  1. Complete Prerequisites: Install Unity3D, VRChat, and all required MCP servers

  2. Install the package: pip install -e ".[dev]"

  3. Add to Cursor MCP configuration using the provided mcpb.json

  4. The server will automatically start when enabled in Cursor

Available Tools (13):

  • robotics_system - System management (help, status, list_robots)

  • robot_control - Unified physical/virtual robot control (Dreame, Yahboom, Elegoo, Hue, virtual)

  • robot_behavior - Advanced robot behavior, animation, and manipulation

  • robot_manufacturing - 3D printing, CNC, laser cutting operations

  • robot_virtual - Virtual robotics environments and testing

  • robot_model_tools - 3D model creation, conversion, and optimization

  • vbot_crud - Virtual robot lifecycle management (create, read, update, delete)

  • drone_control - Core drone flight operations (takeoff, land, move, status)

  • dreame_control - Dreame D20 Pro: vacuum operations + LIDAR map 3D export

  • gazebo_models - Gazebo Fuel: search, download, spawn, manage local models

  • workflow_management - Robotics workflow orchestration and automation

  • virtual_robotics - Legacy virtual robotics operations

  • robot_navigation - Path planning, obstacle avoidance, SLAM

MCP Server Integration

✅ ENABLED WITH SAFETY: Unity3D-MCP is now enabled with robust error handling, timeouts, and fallbacks.

Active Integration:

  • osc-mcp: ✅ ENABLED - OSC communication for real-time robot control

  • unity3d-mcp: ✅ ENABLED - Unity3D integration for virtual robotics

  • vrchat-mcp: ⏸️ DISABLED - VRChat integration (protocol conflicts)

  • avatar-mcp: ⏸️ DISABLED - Avatar management (timeseries conflicts)

  • blender-mcp: ⏸️ DISABLED - 3D model creation (protocol hangs)

  • gimp-mcp: ⏸️ DISABLED - Texture creation (protocol hangs)

Safety Features:

  • 30-second timeouts for server loading

  • 3 retry attempts with exponential backoff

  • Graceful fallbacks to mock operations if Unity unavailable

  • Never blocks robotics-mcp server operation

  • Comprehensive logging for debugging

Configuration: All required MCP servers are automatically loaded with error protection. If Unity is not available, virtual robot operations fall back to mock mode with full functionality preservation.

Configuration (Optional)

The server works out-of-the-box without configuration. For advanced setups, create ~/.robotics-mcp/config.yaml:

robotics: moorebot_scout: enabled: false robot_id: "scout_01" ip_address: "192.168.1.100" port: 9090 mock_mode: true virtual: enabled: true platform: "unity" server: enable_http: true http_port: 12230 log_level: "INFO"

MCP Integration Config (for when mounted servers are re-enabled):

mcp_integration: osc_mcp: enabled: true prefix: "osc" unity3d_mcp: enabled: true prefix: "unity" vrchat_mcp: enabled: true prefix: "vrchat" avatar_mcp: enabled: true prefix: "avatar" blender_mcp: enabled: true prefix: "blender" gimp_mcp: enabled: true prefix: "gimp"

Running the Server

Primary Usage: Configure as MCP server in Cursor IDE using mcpb.json

Manual Operation (Development)

# MCP stdio mode (for testing) python -m robotics_mcp --mode stdio # HTTP API mode python -m robotics_mcp --mode http --port 12230 # Dual mode (stdio + HTTP) python -m robotics_mcp --mode dual --port 12230 # Production mode with crash protection (recommended) .\scripts\run-with-watchfiles.ps1

🛠️ Usage

MCP Tools

Robot Control (7 Robot Types Supported)

Dreame D20 Pro (Primary - Robot Vacuum):

# LIDAR mapping and zone cleaning await robot_control(robot_id="dreame_01", action="get_status") await robot_control(robot_id="dreame_01", action="start_cleaning") await robot_control(robot_id="dreame_01", action="clean_zone", zones=[[0, 0, 500, 300]]) await robot_control(robot_id="dreame_01", action="return_to_dock") await robot_control(robot_id="dreame_01", action="get_map") # Export LIDAR map

Yahboom ROSMASTER (ROS2 Platform):

await robot_control(robot_id="yahboom_01", action="get_status") await robot_control(robot_id="yahboom_01", action="home_patrol") await robot_control(robot_id="yahboom_01", action="camera_capture") await robot_control(robot_id="yahboom_01", action="arm_move", joint_angles={"joint1": 0.0, "joint2": 0.5})

Tdrone Mini (Educational Drone):

# PX4 flight control with waypoint navigation await robot_control(robot_id="tdrone_01", action="takeoff", altitude=3.0) await robot_control(robot_id="tdrone_01", action="goto_waypoint", x=10, y=5, altitude=5) await robot_control(robot_id="tdrone_01", action="set_mode", mode="position_hold") await robot_control(robot_id="tdrone_01", action="return_home")

Philips Hue Bridge Pro (Smart Home):

await robot_control(robot_id="hue_01", action="set_light_state", light_id="1", state={"on": true, "brightness": 200}) await robot_control(robot_id="hue_01", action="activate_scene", scene="bright")

Moorebot Scout (Legacy ROS1):

await robot_control(robot_id="scout_01", action="move", linear=0.2, angular=0.0) await robot_control(robot_id="scout_01", action="stop")

Unitree Go2/G1: Supported when hardware available (stand, sit, walk actions).

Virtual Robotics

# Spawn virtual robot in Unity await virtual_robotics( robot_type="scout", action="spawn_robot", platform="unity", position={"x": 0, "y": 0, "z": 0} ) # Load Marble environment await virtual_robotics( action="load_environment", environment="stroheckgasse_apartment", platform="unity" )

Robot Model Tools

# Create Scout model from scratch (uses blender-mcp + gimp-mcp) await robot_model_create( robot_type="scout", output_path="D:/Models/scout_model.fbx", format="fbx", dimensions={"length": 0.115, "width": 0.10, "height": 0.08}, create_textures=True, texture_style="realistic" ) # Import robot model into Unity await robot_model_import( robot_type="scout", model_path="D:/Models/scout_model.fbx", format="fbx", platform="unity", project_path="D:/Projects/UnityRobots" ) # Convert model between formats await robot_model_convert( source_path="D:/Models/scout.fbx", source_format="fbx", target_format="glb", target_path="D:/Models/scout.glb" )

Drone Control

# Get drone status await drone_control( operation="get_status", drone_id="px4_quad_01" ) # Take off to 5m altitude await drone_control( operation="takeoff", drone_id="px4_quad_01", altitude=5.0 ) # Move drone with velocity control await drone_control( operation="move", drone_id="px4_quad_01", velocity_x=1.0, # 1 m/s forward velocity_y=0.0, # no lateral movement velocity_z=0.0, # no vertical movement yaw_rate=0.1 # slight rotation ) # Arm drone motors await drone_control( operation="arm", drone_id="px4_quad_01" ) # Return to launch position await drone_control( operation="return_home", drone_id="px4_quad_01" )

Drone Streaming

# Start FPV video stream await drone_streaming( operation="start_fpv", drone_id="px4_quad_01", quality="720p" ) # Get stream URL for external viewing stream_info = await drone_streaming( operation="get_stream_url", drone_id="px4_quad_01", protocol="rtsp" ) print(f"Stream URL: {stream_info['url']}") # Start recording video await drone_streaming( operation="start_recording", drone_id="px4_quad_01", filename="flight_2025-01-17.mp4" ) # Take a snapshot await drone_streaming( operation="take_snapshot", drone_id="px4_quad_01", filename="aerial_view.jpg" )

Drone Navigation

# Get current GPS position position = await drone_navigation( operation="get_position", drone_id="px4_quad_01" ) print(f"Lat: {position['latitude']}, Lon: {position['longitude']}, Alt: {position['altitude']}") # Set a waypoint for navigation await drone_navigation( operation="set_waypoint", drone_id="px4_quad_01", latitude=37.7749, longitude=-122.4194, altitude=10.0 ) # Enable follow-me mode await drone_navigation( operation="enable_follow_me", drone_id="px4_quad_01", target_id="operator_gps" ) # Set geofence boundaries await drone_navigation( operation="set_geofence", drone_id="px4_quad_01", fence_points=[ {"lat": 37.7740, "lon": -122.4200}, {"lat": 37.7750, "lon": -122.4200}, {"lat": 37.7750, "lon": -122.4180}, {"lat": 37.7740, "lon": -122.4180} ], max_altitude=30.0 )

Drone Flight Control

# Set flight mode to AUTO await drone_flight_control( operation="set_flight_mode", drone_id="px4_quad_01", mode="AUTO" ) # Get available flight modes modes = await drone_flight_control( operation="get_flight_modes", drone_id="px4_quad_01" ) print(f"Available modes: {modes['modes']}") # Upload a mission plan await drone_flight_control( operation="upload_mission", drone_id="px4_quad_01", mission_plan={ "waypoints": [ {"lat": 37.7749, "lon": -122.4194, "alt": 10.0}, {"lat": 37.7750, "lon": -122.4200, "alt": 15.0} ], "commands": ["takeoff", "waypoint", "land"] } ) # Start mission execution await drone_flight_control( operation="start_mission", drone_id="px4_quad_01", mission_id="recon_mission_01" ) # Tune drone parameters await drone_flight_control( operation="set_parameter", drone_id="px4_quad_01", param_name="WPNAV_SPEED", param_value=500 # cm/s )

Web Interface

The Robotics MCP server includes a modern web-based control panel for easy robot management:

http://localhost:8081

Features:

  • Real-time robot control with intuitive movement buttons

  • Live status monitoring (battery, position, sensors)

  • Camera capture and arm/gripper control

  • Command logging and connection status

  • Responsive design for desktop and mobile

See Web Interface Documentation for detailed usage instructions.

HTTP API

Health Check

curl http://localhost:12230/api/v1/health

List Robots

curl http://localhost:12230/api/v1/robots

Control Robot

curl -X POST http://localhost:12230/api/v1/robots/scout_01/control \ -H "Content-Type: application/json" \ -d '{"action": "move", "linear": 0.2, "angular": 0.0}'

List Tools

curl http://localhost:12230/api/v1/tools

Call Tool

curl -X POST http://localhost:12230/api/v1/tools/robot_control \ -H "Content-Type: application/json" \ -d '{"robot_id": "scout_01", "action": "get_status"}'

📚 Documentation

🛡️ Production & Deployment

🤖 Robot Integration Guides

🔧 Development & Testing

🧪 Testing

Comprehensive test suite: 21 test files, 2,642 lines of tests covering all 11 tools!

# Run all tests pytest # Run unit tests only pytest tests/unit # Run integration tests pytest tests/integration # Run with coverage pytest --cov=robotics_mcp --cov-report=html # Or use the PowerShell script .\scripts\run-tests.ps1

🔧 Development

Project Structure

robotics-mcp/ ├── src/robotics_mcp/ │ ├── server.py # Main FastMCP server │ ├── clients/ # Robot client implementations │ ├── integrations/ # MCP server integration wrappers │ ├── tools/ # Portmanteau tool implementations │ └── utils/ # Utilities (config, state, mock data) ├── tests/ │ ├── unit/ # Unit tests │ └── integration/ # Integration tests ├── docs/ # Documentation ├── scripts/ # Utility scripts └── mcpb/ # MCPB packaging

Code Quality

# Format code black src/ tests/ # Lint code ruff check src/ tests/ # Type checking mypy src/

🔧 Troubleshooting

Cursor MCP Integration Issues

Problem: Server not appearing in Cursor MCP tools

Symptoms:

  • "robotics-mcp" not showing in MCP tools list

  • Tools not available in Cursor

Quick Fix:

  1. Open Cursor Settings → Features → Model Context Protocol

  2. Add new server using the mcpb.json configuration

  3. Ensure the server shows as "Healthy" in the list

  4. Restart Cursor if needed

Server Status Check:

# Verify server starts correctly python -c "from robotics_mcp.server import RoboticsMCP; RoboticsMCP(); print('SUCCESS')"

Configuration File: Use mcpb.json in the project root for Cursor MCP setup.

Other Issues

Server won't start:

  • Check Python version: python --version (requires 3.10+)

  • Verify dependencies: pip install -e ".[dev]"

  • Check logs: C:\Users\sandr\AppData\Roaming\Cursor\logs\

Tools not appearing:

  • Verify MCP server is enabled in Cursor IDE settings

  • Check server logs for errors

  • Try disabling and re-enabling the server

Unity integration not working:

  • Ensure Unity Editor is running

  • Verify Unity project path is correct

  • Check unity3d-mcp server is healthy

🤝 Contributing

Contributions welcome! Please see CONTRIBUTING.md for guidelines.

📄 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

  • FastMCP framework

  • ROS community

  • Unity3D, VRChat, World Labs Marble/Chisel

  • MCP ecosystem contributors

Status: Alpha v0.2.0 (2026-02-08) - FastMCP 2.14+ compliant, Dreame D20 Pro working, Yahboom roslibpy integrated, Gazebo Fuel browser operational, webapp fully navigable.

MCP Server Composition: osc-mcp enabled, unity3d-mcp enabled (with safety), vrchat-mcp/avatar-mcp/blender-mcp/gimp-mcp temporarily disabled for stability.

Deep Analysis: See DEEP_ANALYSIS.md for comprehensive code audit, mock inventory, and bug fix log.

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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