RAGFlow
Integrates with
RAGFlow
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
- Create a new conda environment:
conda create -n ragflow_mcp python=3.12
conda activate ragflow_mcp
- Clone the repository:
git clone https://github.com/oraichain/ragflow-mcp.git
cd ragflow-mcp
- Install dependencies:
pip install -r requirements.txt
Method 2: Using uv (Recommended)
- Install uv (A fast Python package installer and resolver):
curl -LsSf https://astral.sh/uv/install.sh | sh
- Clone the repository:
git clone https://github.com/oraichain/ragflow-mcp.git
cd ragflow-mcp
- 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
- Install dependencies:
uv pip install -r pyproject.toml
Run MCP Server Inspector for debugging
-
Start the MCP server
-
Start the inspector using the following command:
## you can choose a different server
SERVER_PORT=9000 npx @modelcontextprotocol/inspector