Marmot
Discover any data asset in seconds. Then let your AI do the same.
The open-source context layer for your AI. Catalog your tables, topics, queues and APIs then expose real metadata to your AI agents.
Documentation • Deploy • Community
What is Marmot?
Marmot is an open-source data catalog for teams who want powerful data discovery without enterprise complexity. Catalog every data asset, enrich it with the context that matters and make it accessible to your team and your AI tools.
Unlike traditional catalogs that require extensive infrastructure and configuration, Marmot ships as a single binary with an intuitive UI, making it easy to deploy and start cataloging in minutes.
Features
- Search everything: Find any data asset in seconds with full-text search plus structured queries, boolean logic and metadata filters.
- Interactive lineage: Trace data flows from source to destination and analyse impact before making changes.
- Metadata-first: Store rich metadata for any asset type, from tables and topics to APIs and dashboards.
- Team collaboration: Assign ownership, document business context and maintain shared glossaries.
- AI-ready: Expose certified context through MCP, the API and the UI.
Deploy
New to Marmot? Follow the Deploy documentation for a guided setup.
Development
See Local Development for how to get started developing locally.
Join our Discord community for help, feedback and updates on new features.
Contributing
All types of contributions are encouraged and valued!
- Report bugs or suggest features via GitHub Issues
- Improve documentation
- Build new plugins for data sources
Before contributing, please check out the Contributing Guide.
FAQ
What is Marmot?
Marmot is an open-source data catalog for teams who want powerful data discovery without enterprise complexity. It catalogs every data asset (tables, topics, queues, APIs), enriches it with context, and makes it accessible to both your team and AI tools. Unlike traditional catalogs requiring extensive infrastructure, Marmot ships as a single binary with an intuitive UI.
Why Use Marmot?
| Feature | Benefit |
|---|
| Search Everything | Find any data asset in seconds with full-text search, structured queries, boolean logic, and metadata filters |
| Interactive Lineage | Trace data flows from source to destination, analyze impact before making changes |
| Metadata-First | Store rich metadata for any asset type (tables, topics, APIs, dashboards) |
| Team Collaboration | Assign ownership, document business context, maintain shared glossaries |
| AI-Ready | Expose certified context through MCP, API, and UI |
| Single Binary | No complex infrastructure required, deploy in minutes |
How Does Marmot Integrate with AI Agents?
Marmot exposes certified context through MCP (Model Context Protocol), enabling AI agents to query real metadata about your data assets. This allows AI tools to understand your data landscape, trace lineage, and make informed decisions based on actual metadata rather than guessing.
What Data Sources Can I Catalog?
Marmot supports cataloging various data asset types through its plugin system:
- Tables (databases, data warehouses)
- Topics (message queues, event streams)
- Queues (job queues, messaging systems)
- APIs (REST, GraphQL, internal services)
- Dashboards (visualization tools, BI platforms)
How Do I Deploy Marmot?
Quick Start Options:
| Method | Description |
|---|
| Documentation Guide | Follow the Deploy guide for step-by-step setup |
| Single Binary | Download and run the single binary for your platform |
Is Marmot Free?
Yes! Marmot is open-source software licensed under the MIT License. You can use, modify, and distribute it freely. Self-hosting is completely free with no licensing costs.
How Can I Contribute?
All contributions are welcome:
- Report bugs or suggest features via GitHub Issues
- Improve documentation (README, guides, API docs)
- Build new plugins for additional data sources
- Check the Contributing Guide before contributing
Where Can I Get Help?
License
Marmot is open-source software licensed under the MIT License.
