Deep Research MCP

MCP server for Deep Research, enabling AI assistants to perform deep web research and generate comprehensive reports. Built with Machine Core it supports multiple agents in a divide and conquer approach to research. These agents can be edited to behave as you wish, for this reasercher to play a certain persona to research.

for example if you are researching some finace topic, A "Logic" type agent and a "Creative" type will give very different results. you can also just mix and match.

Quick Start with Claude Desktop

Want to use this with Claude Desktop right away? Here's the fastest path:

1. Install dependencies:

   git clone https://github.com/mythrantic/deep-research.git
   pip install -r requirements.txt

2. Set up your Claude Desktop config at ~/Library/Application Support/Claude/claude_desktop_config.json:

   {
     "mcpServers": {
       "gptr-mcp": {
         "command": "python",
         "args": ["/absolute/path/to/deep-research/src/server.py"],
         "env": {
           "OLLAMA_BASE_URL": "your-ollama-base-url-here",
           "LLM_MODEL": "your-llm-model-here"
           // you can use any env var https://github.com/samletnorge/machine-core defines and its dependency. it is the multiagent framework that allows this to work.
         }
       }
     }
   }

3. Restart Claude Desktop and start researching! 🎉

For detailed setup instructions, see the full Claude Desktop Integration section below.

Resources

• research_resource: Get web resources related to a given task via research.

Primary Tools

• deep_research: Performs deep web research on a topic, finding the most reliable and relevant information

• quick_search: Performs a fast web search optimized for speed over quality, returning search results with snippets. Supports any Deep Research supported web retriever such as Tavily, Bing, Google, etc... Learn more here

• write_report: Generate a report based on research results

• get_research_sources: Get the sources used in the research

• get_research_context: Get the full context of the research

Prompts

• research_query: Create a research query prompt

Related MCP server: Harness Research MCP

Prerequisites

• uv/make

⚙️ Installation

1. Clone the repository:

git clone https://github.com/mythrantic/deep-research.git
cd deep-research

2. Install the deep-research dependencies:

cd deep-research
uv sync

3. Set up your environment variables:

   • Copy the .env.example file to create a new file named .env:

   cp .env.example .env

   • Edit the .env file and add your API keys and configure other settings:

You can also add any other env variable allowed by https://github.com/samletnorge/machine-core and its dependencies, such as LLM_PROVIDER etc

🚀 Running the MCP Server

You can run the MCP server in several ways:

Method 1: Directly using Python

python src/server.py
mcp run src/server.py
uv run src/server.py

Method 3: Using Docker (recommended for production)

Quick Start

The simplest way to run with Docker:

# Build and run with docker-compose
docker-compose up -d

# Or manually:
docker build -t deep-research .
docker run -d \
  --name deep-research \
  -p 8000:8000 \
  --env-file .env \
  deep-research