How MCP ROS2 Works
The bridge between AI agents and ROS 2 systems
What MCP ROS2 Enables
Instead of writing custom glue code for each use case, you expose your ROS 2 environment as standard MCP tools that any compatible client can discover and use.
AI-Assisted Debugging
Use AI assistants to inspect, debug and control robots via ROS 2. Ask questions and get structured answers about your robot's state.
Developer Workflows
Build workflows where agents can read topics, call services and publish commands directly from your dev environment.
Monitoring & Analytics
Connect monitoring and analytics tools to ROS 2 data through a consistent interface.
Higher-Level Orchestration
Create orchestration logic on top of WiseOS and your robotic systems.
Core Features
⚡ Simple, Fast Setup
- Installable via
pip, Docker, MCP Market, and dev-tool integrations - Uses stdio transport for minimal configuration overhead
- Designed for rapid prototyping and incremental adoption
🔍 Auto-Discovery of ROS 2 Interfaces
MCP ROS2 automatically discovers ROS 2:
- Topics
- Services
- (Optionally) Actions
...and exposes them as MCP tools, including schema and field definitions. AI agents can dynamically ask what interfaces are available, subscribe/publish to topics, and call services with validated parameters.
🛠️ Semantic, Tool-Oriented Design
Instead of low-level sockets or custom APIs, you interact via MCP tools:
list_topics,subscribe_topic,publish_topiclist_services,call_servicequery_data_black_box(for telemetry via WiseOS / InfluxDB)
This makes MCP ROS2 a natural fit for agentic workflows and integrated dev tools.
🔗 Integration with WiseOS & Data Black Box
When used together with WiseOS:
- MCP ROS2 can access historical and live telemetry from Data Black Box (InfluxDB)
- AI agents can correlate system state with commands and events
- Build powerful debugging and analysis flows
Examples:
- "Check last 100 messages on
/cmd_veland compare with battery voltage." - "Show errors correlated with network latency spikes."
Safety & Governance
MCP ROS2 is designed to be safe for real systems. You remain in control of what AI agents can and cannot do.
🔐 Configurable Access
- Configurable lists of allowed topics and services
- Role-based control over which tools are exposed to which clients
- Ability to restrict write access or sensitive operations
📋 Logging & Auditing
- Logging of tool usage for auditing and post-mortem analysis
- Track what agents did and when
- Full transparency over AI interactions with your robots
Use Cases
🔍 AI-Assisted Debugging
Use an AI assistant to inspect topics, logs and patterns. Ask natural language questions about your robot's behavior.
🗣️ Natural-Language Control
Build voice/chat interfaces for lab robots and demos. Issue commands in plain English.
💻 Developer Tooling
Integrate ROS 2 into IDEs, terminals and dev environments. Reduce context switching.
🛠️ Ops Tooling
Let SRE/ops teams inspect ROS 2 systems without writing custom code. Faster troubleshooting.
Compatible Ecosystem
Works with popular AI platforms and development tools
Claude Desktop
Native integration with Anthropic's Claude
Cursor & VS Code
IDE integrations for dev workflows
MCP-Compatible Clients
Any tool that supports Model Context Protocol
Ecosystem & Availability
Give Your AI Agents and Tools a First-Class Interface to Robotics
Get started with MCP ROS2 and bridge AI and ROS 2