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mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly - MCP Implementation

mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly

Power seamless Model Context Protocol interactions with DuckDB—mcp-server-duckdb bridges databases and AI workflows effortlessly, turning raw data into actionable intelligence.

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About mcp-server-duckdb

What is mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly?

mcp-server-duckdb is a Model Context Protocol (MCP) server that seamlessly integrates DuckDB, a high-performance local database, into AI workflows. It acts as a bridge by exposing database operations via MCP tools, enabling LLMs to execute SQL queries, inspect schemas, and manipulate data directly. Designed for local analysis, this server simplifies the process of leveraging structured data within AI applications without requiring complex middleware.

How to Use mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly?

Getting started involves three key steps:

  1. Install via Smithery: Use the CLI command npx -y @smithery/cli install mcp-server-duckdb --client claude for automatic setup.
  2. Configure in Claude Desktop: Add the server details to the config file with the specified path to your DuckDB database (e.g., "~/mcp-server-duckdb/data/data.db").
  3. Launch and Debug: Run the server and optionally use the MCP Inspector tool for real-time request tracing and error diagnostics.

mcp-server-duckdb Features

Key Features of mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly?

  • Unified MCP Integration: Exposes SQL execution as a first-class citizen in AI workflows through standardized tool APIs.
  • Single-Tool Architecture: Uses a unified execute_sql endpoint to handle all query types, reducing API complexity.
  • Security-first Configuration: Enforces strict path validation for database files and offers optional read-only mode via CLI flags.
  • Local Performance: Leverages DuckDB's in-memory processing for rapid query execution on local datasets.

Use Cases of mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly?

Common scenarios include:

Data-Driven Prompt Engineering

Fetch dynamic query results to construct context-aware prompts for chatbots or analysis tools.

Real-Time Analytics in LLM Chains

Embed live database queries into LangChain workflows for up-to-date statistical insights.

Local Development & Testing

Test AI applications against local datasets without exposing production databases.

mcp-server-duckdb FAQ

FAQ from mcp-server-duckdb: Bridge Database to AI Workflows Effortlessly?

Can I use this with non-DuckDB databases?

Not directly - the server is optimized for DuckDB's in-process architecture. Consider adapters for other systems.

How does security work?

By default, only pre-configured databases are accessible. Read-only mode and path restrictions prevent unintended data modifications.

What about large datasets?

DuckDB's columnar storage handles millions of rows efficiently. For terabyte-scale data, ensure sufficient system memory.

Content

mcp-server-duckdb

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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.

mcp-server-duckdb MCP server

Overview

This server enables interaction with a DuckDB database through the Model Context Protocol, allowing for database operations like querying, table creation, and schema inspection.

Components

Resources

Currently, no custom resources are implemented.

Prompts

Currently, no custom prompts are implemented.

Tools

The server implements the following database interaction tool:

  • 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)

[!NOTE] The server provides a single unified query function rather than separate specialized functions, as modern LLMs can generate appropriate SQL for any database operation (SELECT, CREATE TABLE, JOIN, etc.) without requiring separate endpoints.

[!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 mcp-server-duckdb --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": [
        "mcp-server-duckdb",
        "--db-path",
        "~/mcp-server-duckdb/data/data.db"
      ]
    }
  }
}
  • Note: ~/mcp-server-duckdb/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/mcp-server-duckdb run mcp-server-duckdb --db-path ~/mcp-server-duckdb/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

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