Deep Research Mcp
What is Deep Research Mcp
deep-research-mcp is an MCP server designed for deep research applications, utilizing LangChain to integrate various tools and functionalities.
Use cases
Use cases include automating research workflows, generating research plans, executing complex data queries, and integrating various data sources for comprehensive analysis.
How to use
To use deep-research-mcp, clone the repository, install the necessary dependencies, set up a virtual environment, configure your API keys in a .env file, and run the application using the provided commands.
Key features
Key features include the ability to generate and execute research plans, integration with FastMCP, LangChain, and Groq, and support for easy deployment and configuration.
Where to use
deep-research-mcp can be used in fields such as academic research, data analysis, and any domain requiring deep integration of multiple tools for research purposes.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Deep Research Mcp
deep-research-mcp is an MCP server designed for deep research applications, utilizing LangChain to integrate various tools and functionalities.
Use cases
Use cases include automating research workflows, generating research plans, executing complex data queries, and integrating various data sources for comprehensive analysis.
How to use
To use deep-research-mcp, clone the repository, install the necessary dependencies, set up a virtual environment, configure your API keys in a .env file, and run the application using the provided commands.
Key features
Key features include the ability to generate and execute research plans, integration with FastMCP, LangChain, and Groq, and support for easy deployment and configuration.
Where to use
deep-research-mcp can be used in fields such as academic research, data analysis, and any domain requiring deep integration of multiple tools for research purposes.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Deep Research MCP
This is a sample MCP server used to showcase MCP’s integrative capabilites. It includes two tools: generate_plan and execute_plan.
Built with 🛠
- FastMCP
- LangChain
- Groq
How to run 🏃🏻♂️
-
Clone the repository:
git clone https://github.com/into-the-night/deep-research-mcp.git cd deep-research-mcp -
Install uv:
For Windows-
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"For MacOS/Linux-
curl -LsSf https://astral.sh/uv/install.sh | sh -
Create a virtual environment and activate it:
uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activate -
Install dependencies:
uv pip install -e . -
Create a .env file and populate it with:
TAVILY_API_KEY=<YOUR_TAVILY_API_KEY> GROQ_API_KEY=<YOUR_GROQ_API_KEY> -
Run the app:
uv run app.py
Use with Claude Desktop 💻
-
Download Claue Desktop: https://claude.ai/download
-
Copy and paste this into
claude_desktop_config.json:{ "mcpServers": { "deep_research": { "command": "uv", "args": [ "--directory", "ABSOLUTE\PATH\TO\REPO", "run", "app.py" ] } } } -
Restart Claude Desktop
Note: If you still can’t see the server inside the app, make sure Claude gets completely restarted as it might still be running in system tray.
Author ✍
Made with ♥ by Abhay Shukla
License 📜
This project is licensed under the MIT License - see the LICENSE.md file for details.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
