metadata

title: Rag Mcp Server
emoji: 🏢
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 5.31.0
app_file: app.py
pinned: false
short_description: 'This space defines a RAG MCP server '

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Rag MCP server

This is a simple gradio server that allows you to run a RAG (Retrieval-Augmented Generation) model using the MCP (Model Control Protocol) interface.

Requirements

UV: The python package manager. Visit https://github.com/astral-sh/uv

Since the server uses SERPER API, you will need to set the SERPER_API_KEY environment variable to enable the search functionality. You can export it in your shell:

export SERPER_API_KEY=your_serper_api_key

Installation

uv sync

Usage

Just run the gradio application:

uv run gradio app.py

Access the server

Open your browser and go to http://localhost:7860 to access the RAG MCP server.

You can see the gradio docs for more information on how to use the interface.

Using the MCP server with a mpc client

You can use the tiny-agents client to interact with the MCP server. To do this, you need to install the huggingface_hub package:

pip install huggingface_hub

Then, you can use the following code to interact with the MCP server:

export HF_TOKEN=your_huggingface_token

tiny_agents run agent.json

The agent.json file contains the configuration for the MCP client. Here is an example of how to create this file:

{
  "model": "meta-llama/Llama-3.3-70B-Instruct",
  "provider": "cerebras",
  "servers": [
    {
      "type": "sse",
      "config": {
        "url": "https://frascuchon-rag-mcp-server.hf.space/gradio_api/mcp/sse"
      }
    }
  ]
}

You can change the server URL to point to your own MCP server if you are running it locally or on a different host.