MotherDuck / DuckDB MCP Server

Add to your client

Copy the config for your MCP client and paste it into its config file.

{
  "mcpServers": {
    "motherduck-duckdb-mcp-server": {
      "command": "uvx",
      "args": [
        "mcp-server-motherduck",
        "--db-path",
        "md:"
      ],
      "env": {
        "motherduck_token": "<your-motherduck-token>"
      }
    }
  }
}

Before you start

• Python with the `uv`/`uvx` package manager installed (`pip install uv` or `brew install uv`)
• A DuckDB target: nothing for `:memory:`, a path to a local `.duckdb` file, an S3 URL, or `md:` for MotherDuck
• For MotherDuck connections: a MotherDuck access token from your MotherDuck account (app.motherduck.com), set as `MOTHERDUCK_TOKEN`
• For S3 access: AWS credentials (access key / secret key, optional session token and region)

About MotherDuck / DuckDB MCP Server

Tools & capabilities (5)

When to use it

• Use it when you want an AI assistant to explore and query local CSV/Parquet/JSON files via DuckDB SQL
• Use it when you need to run analytical SQL over data in S3 without loading it into a warehouse
• Use it when you want Claude or Cursor to query your MotherDuck cloud database
• Use it when prototyping data pipelines in an in-memory DuckDB you can read and write to
• Use it when you need quick schema discovery (databases, tables, columns) across multiple DuckDB sources

Quick setup

1. 1Install `uv` (`pip install uv` or `brew install uv`) so `uvx` is available
2. 2Add an `mcpServers` entry to your client running `uvx mcp-server-motherduck` with `--db-path` (e.g. `:memory:`, a file path, an S3 URL, or `md:`)
3. 3For MotherDuck, add `MOTHERDUCK_TOKEN` to the config's `env`; for writes add `--read-write`
4. 4Optionally add `--allow-switch-databases` to enable runtime connection switching
5. 5Restart the MCP client and confirm the DuckDB tools (execute_query, list_tables, etc.) appear

MotherDuck / DuckDB MCP Server FAQ