Autoware MCP Server

Autoware MCP Server

Universal bridge between AI agents and Autoware autonomous driving stack, enabling AI-driven mission planning, real-time vehicle control, and adaptive decision-making.

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Autoware MCP Integration

License ROS2 Autoware

The Autoware MCP Server provides a universal bridge between ANY AI agent (Claude, GPT, Gemini, or custom agents) and the Autoware autonomous driving stack through the Model Context Protocol (MCP). This enables AI-driven mission planning, real-time vehicle control, and adaptive decision-making for autonomous vehicles.

Autonomous Driving Demo

Click the image above to watch the full autonomous driving demo

Key Features

  • Universal AI Support: Works with any MCP-compatible AI agent (Claude, GPT, Gemini, etc.)
  • Full Vehicle Control: Complete control over Autoware's autonomous driving features
  • Real-Time Monitoring: Concurrent monitoring of perception, planning, and vehicle state
  • Launch Management: Start, stop, and manage ROS2 launch sessions
  • Safety Systems: Comprehensive safety validation at every level
  • Mission Execution: Support for complex multi-step missions with waypoints

Quick Start

Prerequisites

  • Ubuntu 22.04 LTS
  • ROS2 Humble
  • Python 3.10+
  • Autoware 0.45.1

Installation

# Clone the repository
git clone https://github.com/your-org/autoware-mcp.git
cd autoware-mcp

# Install uv (Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install dependencies with uv
uv sync --all-extras --dev

Basic Usage

  1. Start the MCP Server:
# Source your ROS2/Autoware workspace
source ~/autoware/install/setup.bash

# Start the MCP server
uv run autoware-mcp
  1. Connect with Claude Code: Add to your Claude Code configuration file (claude_desktop_config.json):
{
  "mcpServers": {
    "autoware": {
      "command": "uv",
      "args": ["run", "autoware-mcp"],
      "env": {
        "ROS_DOMAIN_ID": "your_domain_id"
      }
    }
  }
}
  1. Example Prompts for AI Agents:

Since AI agents may not have specific knowledge about autonomous driving, use clear, step-by-step prompts:

To launch a planning simulation:

Please launch a planning simulation for Autoware using the MCP tools. 
Use the start_launch tool with the planning_simulation_mcp.launch.py file.

To run an autonomous driving sequence:

Please run the complete autonomous driving sequence:
1. Initialize the vehicle's localization at the starting position
2. Clear any existing route and set a new route to the goal position
3. Change the operation mode to autonomous
4. Monitor the vehicle's progress until it reaches the destination
5. Stop the simulation when complete

To monitor vehicle state:

Please check the current vehicle state including position, speed, and route status
using the get_vehicle_state and get_current_route MCP tools.

Available MCP Tools

System Management

  • health_check - Get complete system health status
  • check_autoware_status - Check running Autoware components
  • verify_ros2_environment - Verify ROS2 setup

Launch Management

  • start_launch - Start ROS2 launch files
  • stop_launch - Stop launch sessions
  • list_launch_sessions - View active sessions
  • get_session_status - Get detailed session information

Vehicle Control

  • set_operation_mode - Change between stop/autonomous/local/remote modes
  • initialize_localization - Set initial vehicle pose
  • set_route - Set route to destination
  • set_route_points - Set route with waypoints
  • get_current_route - Get current route status

Vehicle Monitoring

  • get_vehicle_state - Get vehicle position, speed, and kinematics
  • monitor_operation_mode - Monitor current operation mode
  • monitor_localization_state - Check localization status
  • monitor_motion_state - Monitor motion readiness

ROS2 Interface

  • list_ros2_nodes - List all active ROS2 nodes
  • list_ros2_topics - List all ROS2 topics
  • list_ros2_services - List all ROS2 services
  • call_ros2_service - Call any ROS2 service
  • publish_to_topic - Publish to any ROS2 topic
  • echo_topic_messages - Capture messages from topics

Documentation

For comprehensive documentation, please refer to the Developer Guide

Configuration

Create a configuration file config/custom.yaml:

mcp_server:
  host: 0.0.0.0
  port: 8080
  
autoware:
  ros_domain_id: 42
  ad_api_url: http://localhost:8888
  
safety:
  max_velocity: 50.0  # m/s
  max_acceleration: 3.0  # m/s²
  emergency_deceleration: -8.0  # m/s²

Development

Running Tests

# Unit tests
pytest tests/unit -v

# Integration tests (requires Autoware)
pytest tests/integration -v

# Simulation tests
pytest tests/simulation -v

# All tests with coverage
pytest --cov=autoware_mcp --cov-report=html

Contributing

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

Safety Notice

WARNING: This system is designed for research and development purposes. Always ensure:

  • A safety driver is present during real vehicle testing
  • Emergency stop mechanisms are properly configured
  • All safety validations are enabled
  • Testing is conducted in controlled environments

Troubleshooting

Common Issues

  1. ROS2 Connection Issues:
export ROS_DOMAIN_ID=42
export RMW_IMPLEMENTATION=rmw_cyclonedds_cpp
  1. MCP Server Not Responding:
  • Check firewall settings
  • Verify Autoware is running
  • Check logs: tail -f logs/mcp_server.log
  1. Performance Issues:
  • Monitor resource usage: htop, nvidia-smi
  • Check ROS2 topics: ros2 topic hz /topic_name
  • Review latency metrics in Grafana dashboard

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Acknowledgments

Support

For issues and questions:

Roadmap

  • [ ] Multi-vehicle coordination support
  • [ ] Enhanced perception monitoring
  • [ ] Cloud-based mission management
  • [ ] V2X communication integration
  • [ ] Advanced ML-based planning
  • [ ] Simulation environment integration

Note: This project is under active development. APIs and features may change.

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