Skip to main content

A DuckDB MCP server

Project description

mcp-server-duckdb

PyPI - Version PyPI - License smithery badge

A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools. It would be interesting to have LLM analyze it. DuckDB is suitable for local analysis.

Forked from https://github.com/ktanaka101/mcp-server-duckdb

Overview

This server enables interaction with a DuckDB database through the Model Context Protocol, providing a comprehensive set of tools for database operations including:

  • SQL query execution and inspection
  • Table management (creation, description, listing)
  • Data import from various sources (local files, URLs, S3)
  • Data export capabilities
  • Schema inspection and table analysis
  • Statistical summaries of table contents

The server is designed to work seamlessly with Language Models (LLMs) while maintaining data safety through optional read-only mode.

Components

Resources

Currently, no custom resources are implemented.

Prompts

Currently, no custom prompts are implemented.

Tools

The server implements the following database interaction tools:

  • query: Execute any SQL query on the DuckDB database

    • Input: query (string) - Any valid DuckDB SQL statement
    • Output: Query results as text (or success message for operations like CREATE/INSERT)
  • show_tables: Show all tables in the DuckDB database

    • Input: No parameters required
    • Output: List of table names in the database
  • describe_table: Describe a table in the DuckDB database

    • Input: table (string) - Name of table to describe
    • Output: Table schema information
  • inspect_query: Inspect a query in the DuckDB database

    • Input: query (string) - SQL query to inspect
    • Output: Query inspection results
  • create_table_from_path: Create a table from a file path

    • Input:
      • path (string) - Path to the file to load
      • table (string, optional) - Table name to use
      • replace (boolean, optional) - Whether to replace existing table
  • create_table_from_url: Create a table from a URL

    • Input:
      • url (string) - URL to the file to load
      • table (string, optional) - Table name to use
      • replace (boolean, optional) - Whether to replace existing table
  • create_table_from_s3: Create a table from an S3 path

    • Input:
      • path (string) - S3 path to the file to load
      • table (string, optional) - Table name to use
  • create_table_from_csv: Create a table from a CSV file

    • Input:
      • path (string) - Path to the CSV file
      • table (string, optional) - Table name to use
      • delimiter (string, optional) - Delimiter to use
  • summarize_table: Get summary statistics for a table

    • Input: table (string) - Name of table to summarize
    • Output: Statistical summary of the table's contents
  • export_table_to_path: Export a table to a file

    • Input:
      • table (string) - Name of table to export
      • format (string, optional) - Format to export as (default: parquet)
      • path (string, optional) - Path to export to
  • smart_load_multiple_csv_files: Load multiple CSV files and intelligently name the tables

    • Input:
      • paths (array of strings) - List of paths to CSV files
      • delimiter (string, optional) - Delimiter to use for all CSV files
    • Output: Mapping of original table names

[!NOTE] While the server provides specialized functions for common operations, it also maintains the unified query function for maximum flexibility. Modern LLMs can generate appropriate SQL for any database operation (SELECT, CREATE TABLE, JOIN, etc.).

[!NOTE] When the server is running in readonly mode, DuckDB's native readonly protection is enforced. This ensures that the Language Model (LLM) cannot perform any write operations (CREATE, INSERT, UPDATE, DELETE), maintaining data integrity and preventing unintended changes.

Configuration

Required Parameters

  • db-path (string): Path to the DuckDB database file
    • The server will automatically create the database file and parent directories if they don't exist
    • If --readonly is specified and the database file doesn't exist, the server will fail to start with an error

Optional Parameters

  • --readonly: Run server in read-only mode
    • Description: When this flag is set, the server operates in read-only mode. This means:
      • The DuckDB database will be opened with read_only=True, preventing any write operations.
      • If the specified database file does not exist, it will not be created.
      • Security Benefit: Prevents the Language Model (LLM) from performing any write operations, ensuring that the database remains unaltered.
    • Reference: For more details on read-only connections in DuckDB, see the DuckDB Python API documentation.

Installation

Installing via Smithery

To install DuckDB Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install duckdbmcp --client claude

Claude Desktop Integration

Configure the MCP server in Claude Desktop's configuration file:

MacOS

Location: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows

Location: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "duckdb": {
      "command": "uvx",
      "args": [
        "duckdbmcp",
        "--db-path",
        "~/duckdbmcp/data/data.db"
      ]
    }
  }
}
  • Note: ~/duckdbmcp/data/data.db should be replaced with the actual path to the DuckDB database file.

Development

Prerequisites

  • Python with uv package manager
  • DuckDB Python package
  • MCP server dependencies

Debugging

Debugging MCP servers can be challenging due to their stdio-based communication. We recommend using the MCP Inspector for the best debugging experience.

Using MCP Inspector

  1. Install the inspector using npm:
npx @modelcontextprotocol/inspector uv --directory ~/codes/duckdbmcp run duckdbmcp --db-path ~/duckdbmcp/data/data.db
  1. Open the provided URL in your browser to access the debugging interface

The inspector provides visibility into:

  • Request/response communication
  • Tool execution
  • Server state
  • Error messages

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

duckdbmcp-0.0.34.tar.gz (29.9 kB view details)

Uploaded Source

Built Distribution

duckdbmcp-0.0.34-py3-none-any.whl (12.2 kB view details)

Uploaded Python 3

File details

Details for the file duckdbmcp-0.0.34.tar.gz.

File metadata

  • Download URL: duckdbmcp-0.0.34.tar.gz
  • Upload date:
  • Size: 29.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.14

File hashes

Hashes for duckdbmcp-0.0.34.tar.gz
Algorithm Hash digest
SHA256 a0df1d2a7eabe004ba0af537eedb6e67385c0c68c05f03f332da7f2eb5ba5d4e
MD5 14b9e9cb2383ed3319db0920df8b5e4a
BLAKE2b-256 1227282c1ec9bb780f7a371109acc544be33f2093714111013284c61d7569f9c

See more details on using hashes here.

File details

Details for the file duckdbmcp-0.0.34-py3-none-any.whl.

File metadata

File hashes

Hashes for duckdbmcp-0.0.34-py3-none-any.whl
Algorithm Hash digest
SHA256 d364f4f9349ee4f244554b28140846b60fd7c7334cc31db5e8149cf3692c06c6
MD5 a8c3199e246bda9fd749ae4be06122c4
BLAKE2b-256 953fd68e8546644f6306d167eabc0c1abcdec9e2326760bbd4f6232ec703377a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page