mirkosertic/mcpluceneserver

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MCP Lucene Server is a Model Context Protocol (MCP) server that exposes Apache Lucene's full-text search capabilities through a conversational interface.

概要

A Model Context Protocol (MCP) server that exposes Apache Lucene fulltext search capabilities with automatic document crawling and indexing. This server supports both STDIO transport (for Claude Desktop integration) and HTTP transport (for web-based clients and remote access). - Automatically indexes PDFs, Microsoft Office, and OpenOffice documents - Multi-threaded crawling for fast indexing - Real-time directory monitoring for automatic updates - Incremental indexing with full reconciliation (skips unchanged files, removes orphans) - Simple keyword search (no Lucene syntax needed) and full Lucene query syntax search - Field-specific filtering (by author, language, file type, etc.

README

以下は原文 README の抜粋です。原文を見る。

MCP Lucene Server

Features

Automatic Document Crawling

Automatically indexes PDFs, Microsoft Office, and OpenOffice documents
Multi-threaded crawling for fast indexing
Real-time directory monitoring for automatic updates
Incremental indexing with full reconciliation (skips unchanged files, removes orphans)

Powerful Search

Simple keyword search (no Lucene syntax needed) and full Lucene query syntax search
Field-specific filtering (by author, language, file type, etc.)
Structured passages with quality metadata for LLM consumption
Paginated results with filter suggestions

Semantic Search

Optional pure KNN embedding-based semantic search using multilingual-e5 embeddings with Late Chunking
Finds semantically related documents even without exact keyword matches
Requires VECTOR_MODEL to be configured. See SEMANTICSEARCH.md for details.

Query Profiling & Debugging

Deep query analysis and profiling (profileQuery tool)
Understand why queries return certain results and how scoring works
Filter impact analysis showing document reduction per filter
Document scoring explanations with BM25 breakdown
Term statistics (IDF, rarity, document frequency)
Actionable optimization recommendations
LLM-optimized structured output for easy interpretation

Rich Metadata Extraction

Automatic language detection
Author, title, creation date extraction
File type and size information
SHA-256 content hashing for change detection

JDBC Metadata Enrichment

Load additional metadata from PostgreSQL, MySQL, or any JDBC-compatible database at index time
JSON-based metadata with explicit field types (keyword, text, int, long, date)
Multi-value field support, automatic facet registration
Background sync job for incremental metadata updates (configurable interval)
All DB-sourced fields prefixed with dbmeta_ to avoid schema collisions

Text Normalization

Automatic removal of broken/invalid characters (replacement chars, control chars, zero-width chars)
Whitespace normalization (multiple spaces collapsed to single space)
Ensures clean, readable search results and passages

Performance Optimized

Batch processing for efficient indexing
NRT (Near Real-Time) search with dynamic optimization
Configurable thread pools for parallel processing
Progress notifications during bulk operations

Easy Integration

Dual transport support: STDIO (default) and HTTP

GitHub で README 全文を見る

インストール

docker run -v ./lucene-data-dir:/userdata -p 9000:9000 -it mirkosertic42/mcpluceneserver:main

MCP 初心者？mcpskill.org のガイドから始めましょう →

設定

{
  "mcpServers": {
    "lucene-search": {
      "command": "java",
      "args": [
        "--enable-native-access=ALL-UNNAMED",
        "-Xmx2g",
        "-Dspring.profiles.active=deployed",
        "-jar",
        "/absolute/path/to/luceneserver-0.0.1-SNAPSHOT.jar"
      ]
    }
  }
}