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RAGFlow MCP

RAGFlow MCP

Public
oraichain/ragflow-mcp

Lightweight Model Context Protocol server enabling rapid deployment and debugging of RAGFlow integrations with efficient dependency management and virtual environment support.

python
0 tools
May 30, 2025
Updated Jun 4, 2025

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ragflow-mcp

Simple RAGFlow MCP. Only useful until the RAGFlow team releases the official MCP server

Installation

We provide two installation methods. Method 2 (using uv) is recommended for faster installation and better dependency management.

Method 1: Using conda

  1. Create a new conda environment:
conda create -n ragflow_mcp python=3.12
conda activate ragflow_mcp
  1. Clone the repository:
git clone https://github.com/oraichain/ragflow-mcp.git
cd ragflow-mcp
  1. Install dependencies:
pip install -r requirements.txt

Method 2: Using uv (Recommended)

  1. Install uv (A fast Python package installer and resolver):
curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Clone the repository:
git clone https://github.com/oraichain/ragflow-mcp.git
cd ragflow-mcp
  1. Create a new virtual environment and activate it:
uv venv --python 3.12
source .venv/bin/activate  # On Unix/macOS
# Or on Windows:
# .venv\Scripts\activate
  1. Install dependencies:
uv pip install -r pyproject.toml

Run MCP Server Inspector for debugging

  1. Start the MCP server

  2. Start the inspector using the following command:

# you can choose a different server
SERVER_PORT=9000 npx @modelcontextprotocol/inspector
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