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Version: 0.12

Introduction

Marmot gives people and AI agents one governed way in to your data. It catalogs the tables, topics, dashboards and pipelines you already run, records what each one means and who owns it, and serves that context in the web UI, over the API and to agents through its MCP server.

People and agents can also run SQL through Marmot against the sources you connect. Each query is checked against the caller's roles before it reaches the database, and the query audit records who ran what and what came back, so an agent never needs a database password of its own.

Start here​

What you can do with it​

How it fits together​

Plugins read metadata from the systems you already run into one catalog: schemas, owners, descriptions and lineage. People use it in the web UI, agents through the MCP server and your own code through the API, CLI and SDKs, so everyone works from the same answers.

Plugins read metadata from PostgreSQL, Snowflake, BigQuery, Kafka, dbt, Airflow, S3, Looker and more than 60 other systems into Marmot's catalog, glossary, lineage and access rules. People read it in the web UI, agents through the MCP server, and your code through the API, CLI and SDKs.

Where to run it​

Marmot is one Go binary backed by PostgreSQL, and the core is open source under the MIT licence. Everything in these docs applies wherever it runs: the data model, the query language, the plugins and the MCP server are the same in every edition.

Get help​