概览
What is Ragflow Retrieval Mcp Server?
Ragflow Retrieval Mcp Server is an MCP (Model Context Protocol) server that integrates with the RAGFlow knowledge base system to provide content‑based document retrieval capabilities.
How to use Ragflow Retrieval Mcp Server?
Set the required environment variables (SERVER_HOST, SERVER_PORT, RAGFLOW_BASE_URL, RAGFLOW_API_KEY, RAGFLOW_DATASET_ID, and optional RAGFLOW_TOP_K, RAGFLOW_SIMILARITY_THRESHOLD, RAGFLOW_TIMEOUT), then run uvx ragflow-retrieval-mcp-server. For development, create a virtual environment with uv venv, install dependencies with uv pip install -e ., and run with uv run ragflow-retrieval-mcp-server.
Key features of Ragflow Retrieval Mcp Server
- Connects to RAGFlow knowledge base systems.
- Provides content‑based document retrieval.
- Configurable retrieval parameters (top K, similarity threshold, timeout).
- Supports both production and development run modes.
- MIT licensed.
Use cases of Ragflow Retrieval Mcp Server
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FAQ from Ragflow Retrieval Mcp Server
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What are the runtime requirements?
Python 3.10 or higher and a running RAGFlow instance.
How do I configure the server?
Set the environment variables RAGFLOW_BASE_URL, RAGFLOW_API_KEY, and RAGFLOW_DATASET_ID. Optionally set RAGFLOW_TOP_K (default 10), RAGFLOW_SIMILARITY_THRESHOLD (default 0.2), and RAGFLOW_TIMEOUT (default 60).
What transport does the server use?
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Where does the data live?
Data is stored in the connected RAGFlow knowledge base; the server only retrieves results.
Are there any known limitations?
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