Ragflow MCP

Ragflow MCP

RAGFlow MCP is a temporary implementation of an MCP server, providing basic functionality before the official MCP server is released. Two installation methods are provided, and the uv tool is recommended for fast installation and dependency management.

Developer tools Artificial intelligence chatbots #RAG Service #Temporary Solution #Fast Installation #Debugging Tool .Python

rating : 2.5 points

downloads : 8.7K

update time : 2025-04-28

What is RAGFlow MCP?

RAGFlow MCP is a temporary implementation of a Model Context Protocol server designed for the RAGFlow system. It allows communication between different components and is suitable for Retrieval Augmented Generation (RAG) workflows.

How to use RAGFlow MCP?

The server can be installed via conda or the recommended uv package manager. After installation, you can start the server and optionally use the MCP inspector for debugging.

Example Usage

Here are some example commands: ``` # Start the MCP server uv run server.py # Debug using the MCP inspector uv inspect --port 8080 ```

Features

Lightweight Implementation

RAGFlow MCP is a concise and efficient server focused on the communication needs of RAG systems.

Compatibility

Fully compliant with the Model Context Protocol (MCP) standard, seamlessly integrating with various components.

How to Use

Install Dependencies

Use the following command to install the required libraries: ``` pip install mcp - protocol uv ```

Start the MCP Server

Run your MCP server script, such as server.py.

Debug Using the MCP Inspector

Monitor and debug communication via the following command: ``` uv inspect --port 8080 ```

Usage Examples

Frequently Asked Questions

What's the difference between conda and uv installation methods?

When should I use the MCP inspector?

Is this the official MCP server?

Related Resources

uv Documentation

Official documentation for the uv installation tool.

Model Context Protocol

Detailed information about the MCP standard.

GitHub Repository

Open - source implementation of RAGFlow MCP. Contributions are welcome!

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