MCP Lucene.NET

A Model Context Protocol (MCP) server for full-text search using Lucene.NET with document chunking support.

Overview

This project consists of two components:

• /server - MCP server that provides search functionality over a Lucene.NET index
• /idx - CLI tool for indexing documents (text files, PDFs) into Lucene.NET

Quick Start

1. Index Documents

cd idx
dotnet run -- init -i ./lucene-index
dotnet run -- add -d "manual" -t "User Manual" -f "./manual.pdf"
dotnet run -- add -d "policy" -t "Privacy Policy" -c "Our privacy policy..."

2. Start MCP Server

cd server
dotnet run ./lucene-index

3. Search Documents

The server exposes a Search tool that returns JSON with relevant document chunks.

MCP Configuration

To configure the server in Claude Desktop or other MCP clients, add this to your MCP configuration:

{
  "mcpServers": {
    "lucene-search": {
      "command": "/path/to/mcp-lucene-net/server/bin/Release/net8.0/server",
      "args": [
        "/path/to/your/lucene-index"
      ],
      "env": {}
    }
  }
}

Replace /path/to/mcp-lucene-net/server/bin/Release/net8.0/server with the actual path to your compiled server binary and /path/to/your/lucene-index with the path to your Lucene index directory.

Document Chunking

Documents are automatically split into ~250 word chunks with 40 word overlap to optimize search relevance and LLM context usage. Each chunk includes:

• id: Unique chunk identifier (e.g., "manual-chunk-001")
• title: Descriptive title with part number
• content: ~250 words of text
• source_document: Original document ID
• chunk_index: Sequential chunk number

CLI Commands

# Initialize new index
idx init -i ./lucene-index

# Add single document
idx add -d "doc1" -t "Title" -c "Text content"
idx add -d "doc2" -t "Title" -f "./document.pdf"

# Bulk add from JSON
idx bulk -i ./lucene-index -j "./documents.json"

JSON Format

[
  {
    "Id": "doc1",
    "Title": "Document Title",
    "Content": "Document content..."
  }
]

Requirements

• .NET 8.0
• Lucene.NET 4.8.0-beta
• iText for PDF extraction