Open Deep Research MCP Server

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An AI-powered research assistant that performs deep, iterative research on any topic. It combines search engines, web scraping, and AI to explore topics in depth and generate comprehensive reports. Available as a Model Context Protocol (MCP) tool or standalone CLI.

Quick Start

Clone and install:


git clone https://github.com/Ozamatash/deep-research
cd deep-research
npm install

Set up environment in .env.local:


# Copy the example environment file
cp .env.example .env.local

Build:


# Build the server
npm run build

Run the cli version:


npm run start "Your research query here"

Test MCP Server with Claude Desktop:
Follow the guide thats at the bottom of server quickstart to add the server to Claude Desktop:
https://modelcontextprotocol.io/quickstart/server

Features

Performs deep, iterative research by generating targeted search queries
Controls research scope with depth (how deep) and breadth (how wide) parameters
Generates follow-up questions to better understand research needs
Produces detailed markdown reports with findings and sources
Available as a Model Context Protocol (MCP) tool for AI agents
For now MCP version doesn’t ask follow up questions

How It Works

Advanced Setup

Using Local Firecrawl (Free Option)

Instead of using the Firecrawl API, you can run a local instance. You can use the official repo or my fork which uses searXNG as the search backend to avoid using a searchapi key:

Set up local Firecrawl:


git clone https://github.com/Ozamatash/localfirecrawl
cd localfirecrawl
# Follow setup in localfirecrawl README

Update .env.local:


FIRECRAWL_BASE_URL="http://localhost:3002"

Optional: Observability

Add observability to track research flows, queries, and results using Langfuse:


# Add to .env.local
LANGFUSE_PUBLIC_KEY="your_langfuse_public_key"
LANGFUSE_SECRET_KEY="your_langfuse_secret_key"

The app works normally without observability if no Langfuse keys are provided.

License

MIT License