rag-mcp-server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@rag-mcp-serverWhat does the paper say about ocean warming?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
RAG MCP Server
MCP Server that gives Claude Code semantic search over your PDFs, code, and documents. Index once, query instantly — with exact citations and zero hallucinations.
Setup
1. Install
git clone https://github.com/Rubrum95/rag-mcp-server
cd rag-mcp-server
pip install .For OCR support (scanned PDFs):
pip install ".[ocr]"
# macOS
brew install tesseract
# Windows — download installer from:
# https://github.com/UB-Mannheim/tesseract/wiki
# Linux
sudo apt install tesseract-ocr tesseract-ocr-spa2. Connect to Claude Code
Add to ~/.claude/settings.json:
{
"mcpServers": {
"rag": {
"command": "rag-mcp-server"
}
}
}Related MCP server: Claude RAG MCP Pipeline
Usage
Index a project
Ask Claude: "Index ~/projects/my-research"
→ Calls rag_index, processes all PDFs and code filesQuery documents
Ask Claude: "What does the paper say about ocean warming?"
→ Calls rag_query, returns exact text with page citationsUpdate with new files
Ask Claude: "Update the my-research index"
→ Calls rag_update, only processes new/changed filesList indexed projects
Ask Claude: "List my indexed projects"
→ Shows all projects with file/chunk countsConfiguration
Copy config.yaml to ~/.rag-mcp-server/config.yaml to customize:
embedding_model— default: multilingual model (Spanish + English)chunk_size/chunk_overlap— text splitting parameterstop_k— default number of search resultsocr_languages— Tesseract languages for scanned PDFssupported_extensions— file types to index
How It Works
Your files → Text extraction → Chunking → Embeddings → ChromaDB
(+ OCR if needed)
Your question → Embedding → Cosine similarity search → Top chunks
↓
Claude reads exact text
and responds with citationsRequirements
Python 3.10+
~500MB disk for embedding model (downloaded once)
Tesseract (optional, for scanned PDFs)
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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