Deep Research MCP Server

Deep Research is an agent-based tool that provides web search and advanced research capabilities. It leverages HuggingFace's smolagents and is implemented as an MCP server.

This project is based on HuggingFace's open_deep_research example.

Features

• Web search and information gathering
• PDF and document analysis
• Image analysis and description
• YouTube transcript retrieval
• Archive site search

Environment Variables

Create a .env file in the root directory of the project and set the following environment variables:

OPENAI_API_KEY=your_openai_api_key
HF_TOKEN=your_huggingface_token
SERPER_API_KEY=your_serper_api_key

You can obtain a SERPER_API_KEY by signing up at Serper.dev.

Key Components

• deep_research.py: Entry point for the MCP server
• create_agent.py: Agent creation and configuration
• scripts/: Various tools and utilities
  • text_web_browser.py: Text-based web browser
  • text_inspector_tool.py: File inspection tool
  • visual_qa.py: Image analysis tool
  • mdconvert.py: Converts various file formats to Markdown

License

This project is provided under the Apache License 2.0.

Acknowledgements

This project uses code from HuggingFace's smolagents and Microsoft's autogen projects.

Requirements

• Python 3.11 or higher
• uv package manager
• The following API keys:
  • OpenAI API key
  • HuggingFace token
  • SerpAPI key

Installation

1. Clone the repository:

git clone https://github.com/Hajime-Y/deep-research-mcp.git
cd deep-research-mcp

2. Create a virtual environment and install dependencies:

uv venv
source .venv/bin/activate # For Linux or Mac
# .venv\Scripts\activate # For Windows
uv sync

Usage

Start the MCP server:

uv run deep_research.py

This will launch the deep_research agent as an MCP server.

Docker Usage

You can also run this MCP server in a Docker container:

# Build the Docker image
docker build -t deep-research-mcp .

# Run with required API keys
docker run -p 8080:8080 \
  -e OPENAI_API_KEY=your_openai_api_key \
  -e HF_TOKEN=your_huggingface_token \
  -e SERPER_API_KEY=your_serper_api_key \
  deep-research-mcp

Registering with MCP Clients

To register this Docker container as an MCP server in different clients:

Claude Desktop

Add the following to your Claude Desktop configuration file (typically located at ~/.config/Claude/claude_desktop_config.json on Linux, ~/Library/Application Support/Claude/claude_desktop_config.json on macOS, or %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "deep-research-mcp": {
      "command": "docker",
      "args": [
        "run", 
        "-i", 
        "--rm", 
        "-e", "OPENAI_API_KEY=your_openai_api_key",
        "-e", "HF_TOKEN=your_huggingface_token", 
        "-e", "SERPER_API_KEY=your_serper_api_key",
        "deep-research-mcp"
      ]
    }
  }
}

Cursor IDE

For Cursor IDE, add the following configuration:

{
  "mcpServers": {
    "deep-research-mcp": {
      "command": "docker",
      "args": [
        "run", 
        "-i", 
        "--rm", 
        "-e", "OPENAI_API_KEY=your_openai_api_key",
        "-e", "HF_TOKEN=your_huggingface_token", 
        "-e", "SERPER_API_KEY=your_serper_api_key",
        "deep-research-mcp"
      ]
    }
  }
}

Using with Remote MCP Server

If you're running the MCP server on a remote machine or exposing it as a service, you can use the URL-based configuration:

{
  "mcpServers": {
    "deep-research-mcp": {
      "url": "http://your-server-address:8080/mcp",
      "type": "sse"
    }
  }
}