Flexible GraphRAG — Backend + MCP for Docs

Main

• Treat it as two layers: backend REST API first, then MCP server connecting to it (README requires backend on :8000).

• Start with the smallest footprint: install from PyPI and run flexible-graphrag before enabling optional databases/extras.

• Use MCP Inspector for debugging: README suggests npx @modelcontextprotocol/inspector to validate tools over Streamable HTTP.

• Scale ingestion sources gradually: README states 13 data sources and 9 MCP tools; add sources only after your baseline pipeline works.

Source-backed notes

• README states the backend is a FastAPI service at http://localhost:8000 and includes Angular/React/Vue frontends.
• README says the MCP server provides 9 specialized tools and supports all 13 data sources via backend REST APIs.
• README MCP quickstart runs flexible-graphrag-mcp --http --port 3001 and tests with npx @modelcontextprotocol/inspector.

FAQ

• Do I need the backend running for MCP?: Yes — README says the MCP server connects to the backend REST API; it must be up on http://localhost:8000.
• What’s a good first validation step?: Use MCP Inspector (npx @modelcontextprotocol/inspector) in HTTP mode as shown in README.
• How many tools and sources are covered?: README states 9 MCP tools and 13 data sources supported by the pipeline.