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FinRAG-MCP

FinRAG-MCP is a Role-Based Access Control (RBAC) Retrieval-Augmented Generation (RAG) system, integrated with the Model Context Protocol (MCP).
It lets you query company documents (Engineering, Finance, HR, Marketing, General) securely — each role only sees what it’s allowed to.

✅ Works with Claude Desktop (MCP tools)
✅ Optional Streamlit UI + FastAPI gateway
✅ Uses Qdrant (local) for vector search
✅ Documents enriched with metadata + citations


🚀 Why this project

  • Secure answers → Employees, Managers, and C-Level see different data (RBAC).

  • Trusted output → Every response includes sources and file chunks.

  • Flexible → Claude MCP integration + standalone UI.

  • Practical → Handles Markdown, CSV, reports, handbooks, financial summaries.


📂 Project Structure

FinRAG-MCP

FinRAG-MCP is a Role-Based Access Control (RBAC) Retrieval-Augmented Generation (RAG) system, integrated with the Model Context Protocol (MCP).
It lets you query company documents (Engineering, Finance, HR, Marketing, General) securely — each role only sees what it’s allowed to.

✅ Works with Claude Desktop (MCP tools)
✅ Optional Streamlit UI + FastAPI gateway
✅ Uses Qdrant (local) for vector search
✅ Documents enriched with metadata + citations


🚀 Why this project

  • Secure answers → Employees, Managers, and C-Level see different data (RBAC).

  • Trusted output → Every response includes sources and file chunks.

  • Flexible → Claude MCP integration + standalone UI.

  • Practical → Handles Markdown, CSV, reports, handbooks, financial summaries.


📂 Project Structure


⚙️ Setup

``bash

Clone repo

git clone https://github.com/YOUR_GITHUB/finrag-mcp.git cd finrag-mcp

Create venv with uv

uv venv .venv source .venv/bin/activate uv sync

Add secrets

cat > env/.env << 'EOF' OPENAI_API_KEY=sk-REPLACE_ME OPENAI_MODEL=gpt-4o-mini EMBED_MODEL=text-embedding-3-large QDRANT_LOCAL_PATH=.qdrant_local QDRANT_COLLECTION_PREFIX=finrag FINRAG_ROLE=EMPLOYEE EOF

Ingest docs

uv run python -m ingest.run_ingest --data-root ./data

Run Options

  1. Claude MCP (Recommended) Open Claude Desktop → Settings → Developer → Local MCP servers Add: Command: .../finrag-mcp/.venv/bin/python Args: -m mcp_server.server Env: from .env Claude can now call tools: set_role("FINANCE") search("Q4 2024 revenue drivers", top_k=5)

Start gateway

uv run uvicorn gateway.app:app --port 8000

Start UI

uv run streamlit run ui/app.py --server.port 8501

Example Queries Employee: “What does the handbook say about leave approval?” Engineering: “List services in the architecture doc.” Finance: “Summarize Q4 revenue drivers.” HR: “What’s the rule for sick leave >2 days?” Marketing: “Which 2024 campaigns had the best ROI?”

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security - not tested
F
license - not found
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quality - not tested

MCP directory API

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/Nithishkaranam2002/Finrag--mcp'

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