Lightning-Fast, High-Accuracy Deep Research Agent π 8β10x faster π Greater depth & accuracy π Unlimited parallel runs
The Octagon Deep Research MCP server provides specialized AI-powered comprehensive research and analysis capabilities by integrating with advanced deep research agents. No rate limits, faster than ChatGPT Deep Research, more thorough than Grok DeepSearch or Perplexity Deep Research. Add unlimited deep research functionality to any MCP client including Claude Desktop, Cursor, and other popular MCP-enabled applications.
Powered by Octagon AI - Learn more about the Deep Research Agent at docs.octagonagents.com
π 8β10x faster than the leading incumbentβcomplex analyses complete in seconds, not minutes
π Greater depth & accuracy βpulls data from 3x more high-quality sources and cross-checks every figure
π Unlimited parallel runsβno rate caps, so your analysts can launch as many deep-dive tasks as they need (unlike ChatGPT Pro's 125-task monthly limit)
β
No Rate Limits - Execute unlimited deep research queries without restrictions (vs ChatGPT Pro's 125-task monthly limit)
β
Superior Performance - Faster than ChatGPT Deep Research, more thorough than Grok DeepSearch or Perplexity Deep Research
β
Enterprise-Grade Speed - 8-10x faster than leading incumbents, with 3x more source coverage
β
Universal MCP Integration - Add deep research functionality to any MCP client
β
Multi-Domain Expertise - Comprehensive research across any topic or industry
β
Advanced Data Synthesis - Multi-source aggregation with cross-verification of every figure
β Comprehensive Research Capabilities
β Universal Domain Coverage
β Advanced Analysis Tools
To use Octagon Deep Research MCP, you need to:
OCTAGON_API_KEY
valueBefore installing or running Octagon Deep Research MCP, you need to have npx
(which comes with Node.js and npm) installed on your system.
Install Homebrew (if you don't have it):
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
Install Node.js (includes npm and npx):
brew install node
This will install the latest version of Node.js, npm, and npx.
Verify installation:
node -v
npm -v
npx -v
node -v
npm -v
npx -v
If you see version numbers for all three, you are ready to proceed with the installation steps below.
To configure Octagon Deep Research MCP for Claude Desktop:
claude_desktop_config.json
(Replace your-octagon-api-key
with your Octagon API key):{
"mcpServers": {
"octagon-deep-research-mcp": {
"command": "npx",
"args": ["-y", "octagon-deep-research-mcp@latest"],
"env": {
"OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
Configuring Cursor Desktop π₯οΈ Note: Requires Cursor version 0.45.6+
To configure Octagon Deep Research MCP in Cursor:
env OCTAGON_API_KEY=your-octagon-api-key npx -y octagon-deep-research-mcp
If you are using Windows and are running into issues, try
cmd /c "set OCTAGON_API_KEY=your-octagon-api-key && npx -y octagon-deep-research-mcp"
Replace your-octagon-api-key
with your Octagon API key.
After adding, refresh the MCP server list to see the new tools. The Composer Agent will automatically use Octagon Deep Research MCP when appropriate, but you can explicitly request it by describing your research needs. Access the Composer via Command+L (Mac), select "Agent" next to the submit button, and enter your query.
Add this to your ./codeium/windsurf/model_config.json
:
{
"mcpServers": {
"octagon-deep-research-mcp": {
"command": "npx",
"args": ["-y", "octagon-deep-research-mcp@latest"],
"env": {
"OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
env OCTAGON_API_KEY=your_octagon_api_key npx -y octagon-deep-research-mcp
npm install -g octagon-deep-research-mcp
For comprehensive documentation on using Deep Research capabilities, please visit our official documentation at: https://docs.octagonagents.com
Specifically for the Deep Research Agent: Deep Research Agent Guide
The documentation includes:
Comprehensive deep research and analysis across any topic or domain.
The tool uses a single prompt
parameter that accepts a natural language query. Include all relevant details in your prompt for optimal results.
MIT
β Star this repo if you find it helpful for your research needs!
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