datasette-mcp

datasette-mcp

Adds an MCP server to a Datasette instance, exposing tools to list databases, retrieve database schemas, and execute read-only SQL queries.

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datasette-mcp

PyPI Changelog Tests License

Adds a /-/mcp MCP server to any Datasette instance

Installation

Install this plugin in the same environment as Datasette.

datasette install datasette-mcp

Usage

Start Datasette as normal, then configure an MCP client to connect to:

http://localhost:8001/-/mcp

The endpoint uses MCP Streamable HTTP and exposes three read-only tools by default:

  • list_databases lists the databases available to the current Datasette actor.
  • get_database_schema returns the complete SQL schema for a database, including tables, indexes, views, and triggers.
  • execute_sql executes one read-only SQL statement and returns structured columns, rows, and a truncation indicator.

Datasette database visibility and execute-sql permissions are enforced for every tool call. SQL uses the same validate_sql_select() and read-only Database.execute() path as Datasette's custom SQL interface.

Registering additional MCP tools

Other Datasette plugins can add tools to this MCP server by implementing the register_mcp_tools(datasette, mcp) plugin hook. The mcp argument is the MCPServer for that Datasette instance, so implementations use the MCP Python SDK's normal @mcp.tool() decorator:

from datasette import hookimpl


@hookimpl
def register_mcp_tools(datasette, mcp):
    @mcp.tool()
    async def database_count() -> int:
        """Return the number of user-facing databases."""
        return len(
            [name for name in datasette.databases if name != "_internal"]
        )

The hook itself is synchronous because tools are registered while the MCP server is being constructed. Tool functions can be synchronous or asynchronous and can use all of the input, output, context, and annotation features provided by the MCP Python SDK.

Datasette-mcp registers list_databases, get_database_schema, and execute_sql through this same hook.

Development

To set up this plugin locally, first checkout the code. You can confirm it is available like this:

cd datasette-mcp
# Confirm the plugin is visible
uv run datasette plugins

To run the tests:

uv run pytest

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