Deep Research
About
Provides web search and advanced research capabilities with specialized tools for browsing, document analysis, media processing, and archive searching to gather information from diverse sources.
Details
- Repository
- Hajime-Y/deep-research-mcp
- License
- Apache-2.0
Explore
- Web search and information gathering
- PDF and document analysis
- Image analysis and description
- YouTube transcript retrieval
- Archive site search
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Deep ResearchCommand (node, npx, python, etc.)dockerArguments-
Argument 1
run -
Argument 2
-i -
Argument 3
--rm -
Argument 4
-e -
Argument 5
OPENAI_API_KEY=your_openai_api_key -
Argument 6
-e -
Argument 7
HF_TOKEN=your_huggingface_token -
Argument 8
-e -
Argument 9
SERPER_API_KEY=your_serper_api_key -
Argument 10
deep-research-mcp
Environment-
HF_TOKEN
your_huggingface_token -
OPENAI_API_KEY
your_openai_api_key -
SERPER_API_KEY
your_serper_api_key
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Start the MCP server:
uv run deep_research.py
This will launch the deep_research agent as an MCP server.
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.
You can also run this MCP server in a Docker container:
```bash
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"deep research": {
"env": {
"HF_TOKEN": "your_huggingface_token",
"OPENAI_API_KEY": "your_openai_api_key",
"SERPER_API_KEY": "your_serper_api_key"
},
"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"
],
"command": "docker"
}
}
}Linux
{
"env": {
"HF_TOKEN": "your_huggingface_token",
"OPENAI_API_KEY": "your_openai_api_key",
"SERPER_API_KEY": "your_serper_api_key"
},
"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"
],
"command": "docker"
}Macos
{
"env": {
"HF_TOKEN": "your_huggingface_token",
"OPENAI_API_KEY": "your_openai_api_key",
"SERPER_API_KEY": "your_serper_api_key"
},
"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"
],
"command": "docker"
}Windows
{
"env": {
"HF_TOKEN": "your_huggingface_token",
"OPENAI_API_KEY": "your_openai_api_key",
"SERPER_API_KEY": "your_serper_api_key"
},
"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"
],
"command": "docker"
}Deep Research is an agent-based tool that provides web search and advanced research capabilities. It leverages HuggingFace'ssmolagentsand is implemented as an MCP server.
This project is based onHuggingFace's open_deep_research example.
- Web search and information gathering
- PDF and document analysis
- Image analysis and description
- YouTube transcript retrieval
- Archive site search
- Python 3.11 or higher
- uvpackage manager
- The following API keys:
- OpenAI API key
- HuggingFace token
- SerpAPI key
git clone https://github.com/Hajime-Y/deep-research-mcp.git cd deep-research-mcp
- Create a virtual environment and install dependencies:
uv venv source .venv/bin/activate # For Linux or Mac # .venv\Scripts\activate # For Windows uv sync
Create a.envfile 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 atSerper.dev.
This will launch thedeep_researchagent as an MCP server.
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
To register this Docker container as an MCP server in different clients:
Add the following to your Claude Desktop configuration file (typically located at~/.config/Claude/claude_desktop_config.jsonon Linux,~/Library/Application Support/Claude/claude_desktop_config.jsonon macOS, or%APPDATA%\Claude\claude_desktop_config.jsonon 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" ] } } }
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" ] } } }
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" } } }
- 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
This project is provided under the Apache License 2.0.
This project uses code from HuggingFace'ssmolagentsand Microsoft'sautogenprojects.
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