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DuckDB-RAG-MCP-Sample

by nananaman
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Python
Hybrid
Apache 2.0
4
  • Apple

DuckDB RAG MCP Sample

This is a sample that embeds and vectorizes a markdown document so that it can be explained using MCP and RAG.

We use Plamo-Embedding-1B for vectorization.

function

  • Extract and vectorize text from markdown files

  • Vector Searching with DuckDB

  • Persisting vector data with Parquet files

  • Vector search from MCP

How to use

Vector data generation

First, place the markdown files you want to search in a specific directory, then convert them to Parquet files with the following command.

uv run main.py --directory ~/path/to/markdown/files --parquet vectors.parquet

Configuring MCP

Build

The following command will generate a single binary in dist/server .

uv run pyinstaller --clean --strip --noconfirm --onefile server.py

MCP Client Configuration

Please set it according to the client you want to use.

For Claude Desktop it looks like this:

For VECTOR_PARQUET, specify the file you just converted.

uv run mcp install server.py -v VECTOR_PARQUET=/path/to/vectors.parquet

It is set as follows:

{ "mcpServers": { "DuckDB-RAG-MCP-Sample": { "command": "/path/to/dist/server", "env": { "VECTOR_PARQUET": "/path/to/vectors.parquet" } } } }

Start the development server

uv run mcp dev server.py

license

The DuckDB RAG MCP Sample is provided under the Apache License, Version 2.0.

This server cannot be installed

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security - not tested
A
license - permissive license
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quality - not tested

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