Rag MCP server

FieldCure MCP RAG Server

A Model Context Protocol (MCP) server for indexing and searching local document collections. Supports DOCX, HWPX, PDF (with OCR), Excel, PowerPoint, and audio (Whisper transcription, Windows-only), with hybrid keyword + semantic search optimized for Korean and English.

Built with C# and the official MCP C# SDK.

Commands

fieldcure-mcp-rag
├── serve         --base-path <path>                         # Multi-KB MCP search server (stdio)
├── exec          --path <kb-path> [--force] [--partial ...]  # Headless indexing for a single KB
├── exec-queue    --queue-file <path> [--sweep-all]           # Process deferred indexing queue
├── prune-orphans --base-path <path>                         # Delete orphan KB folders
└── smoke-ocr     --pdf <scanned.pdf>                        # Self-test: OCR a scanned PDF (Windows)

• serve — read-only MCP server serving all knowledge bases under the base path. Single process handles multiple KBs via kb_id parameter. Can run while exec is indexing (SQLite WAL).
• exec — scans source folders, chunks documents, contextualizes with AI, embeds, stores in SQLite. --partial re-runs only downstream stages when models change, preserving OCR output.
• exec-queue — sequential orchestrator consuming a deferred indexing queue. One entry at a time, no GPU contention. --sweep-all processes deferred entries too (used at app shutdown).
• prune-orphans — deletes orphan KB folders (GUID-named, no config.json). Protected folders (., _ prefix, -backup-) are never touched.
• smoke-ocr — diagnostic mode. Loads a scanned PDF through the OCR fallback parser, prints recognized text to stdout, and exits 0 on a non-empty result. Surfaces DllNotFoundException / BadImageFormatException distinctly so a missing or arch-mismatched native is immediately visible. Useful for verifying that the OCR native path is wired correctly on a given host (notably win-arm64 dnx installs).

Features

Search

• Hybrid BM25 + vector search with Reciprocal Rank Fusion (RRF)
• BM25-only fallback when no embedding provider is configured
• Korean-optimized chunking (sentence boundary, decimal protection, parenthesis-aware)
• SIMD-accelerated cosine similarity via System.Numerics.Vector
• FTS5 trigram index for substring and CJK-friendly keyword matching

Indexing

• Incremental indexing with SHA256 change detection
• AI-powered chunk contextualization with bilingual keyword enrichment (see Chunk Contextualization)
• 2-commit pipeline preserves expensive upstream work across embedding failures (see How Indexing Works)
• Math equation extraction from DOCX/HWPX as [math: LaTeX] blocks
• PDF with OCR fallback (Tesseract eng+kor) for scanned pages
• Audio transcription (.mp3, .wav, .m4a, .ogg, .flac, .webm) via Whisper.net — Windows-only. Model size (Tiny→Large) is auto-selected from detected GPU/RAM/cores at startup; each transcript chunk records audio.modelsize and audio.transcribedat for future reindex auditing
• Cross-process indexing lock with stale PID auto-cleanup
• Orphan cleanup for deleted files

Queue Orchestrator

• All indexing requests flow through start_reindex MCP tool — no direct exec spawn
• Scope merge rules: full ⊃ contextualization ⊃ embedding (duplicate requests upgrade, not duplicate)
• PID-based orchestrator lock with reuse defense (orchestrator.lock)
• Logical KB deletion (config.json removal) + prune-orphans physical cleanup
• Deferred indexing for app-shutdown batch processing (--sweep-all)

Shortened. The full README is on GitHub.