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Octagon Deep Research MCP

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Octagon Deep Research MCP

Favicon 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

Demo

๐Ÿ† Why Teams Choose Octagon's Enterprise-Grade Deep Research API

๐Ÿ‘‰ 8โ€“10x faster than the leading incumbentโ€”complex analyses complete in seconds, not minutes
๐Ÿ‘‰ Greater depth & accuracy โ€”pulls data from 3x more high-quality sources and cross-checks every figure
๐Ÿ‘‰ Unlimited parallel runsโ€”no rate caps, so your analysts can launch as many deep-dive tasks as they need (unlike ChatGPT Pro's 125-task monthly limit)

Related MCP server: GPT Researcher MCP Server

๐Ÿš€ Core Differentiators

โœ… No Rate Limits - Execute unlimited deep research queries without restrictions (vs ChatGPT Pro's 125-task monthly limit)
โœ… Superior Performance - Faster than ChatGPT Deep Research, more thorough than Grok DeepSearch or Perplexity Deep Research
โœ… Enterprise-Grade Speed - 8-10x faster than leading incumbents, with 3x more source coverage
โœ… Universal MCP Integration - Add deep research functionality to any MCP client
โœ… Multi-Domain Expertise - Comprehensive research across any topic or industry
โœ… Advanced Data Synthesis - Multi-source aggregation with cross-verification of every figure

Features

โœ… Comprehensive Research Capabilities

  • Multi-source data aggregation and synthesis

  • Academic research and literature review

  • Competitive landscape analysis

  • Market intelligence and trend analysis

  • Technical and scientific research

  • Policy and regulatory research

  • Real-time web scraping and data extraction

โœ… Universal Domain Coverage

  • Technology and AI research

  • Healthcare and medical research

  • Environmental and sustainability studies

  • Economic and business analysis

  • Scientific and engineering research

  • Social and cultural studies

  • Political and policy analysis

โœ… Advanced Analysis Tools

  • Comprehensive report generation

  • Cross-source verification

  • Trend identification and forecasting

  • Comparative analysis frameworks

Get Your Octagon API Key

To use Octagon Deep Research MCP, you need to:

  1. Sign up for a free account at Octagon

  2. After logging in, from left menu, navigate to API Keys

  3. Generate a new API key

  4. Use this API key in your configuration as the OCTAGON_API_KEY value

Prerequisites

Before installing or running Octagon Deep Research MCP, you need to have npx (which comes with Node.js and npm) installed on your system.

Mac (macOS)

  1. Install Homebrew (if you don't have it):

    /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
  2. Install Node.js (includes npm and npx):

    brew install node

    This will install the latest version of Node.js, npm, and npx.

  3. Verify installation:

    node -v
    npm -v
    npx -v

Windows

  1. Download the Node.js installer:

  2. Run the installer and follow the prompts. This will install Node.js, npm, and npx.

  3. Verify installation: Open Command Prompt and run:

    node -v
    npm -v
    npx -v

If you see version numbers for all three, you are ready to proceed with the installation steps below.

Installation

Running on Claude Desktop

To configure Octagon Deep Research MCP for Claude Desktop:

  1. Open Claude Desktop

  2. Go to Settings > Developer > Edit Config

  3. Add the following to your 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"
      }
    }
  }
}
  1. Restart Claude for the changes to take effect

Running on Cursor

Configuring Cursor Desktop ๐Ÿ–ฅ๏ธ Note: Requires Cursor version 0.45.6+

To configure Octagon Deep Research MCP in Cursor:

  1. Open Cursor Settings

  2. Go to Features > MCP Servers

  3. Click "+ Add New MCP Server"

  4. Enter the following:

    • Name: "octagon-deep-research-mcp" (or your preferred name)

    • Type: "command"

    • Command: 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.

Running on Windsurf

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"
      }
    }
  }
}

Running with npx

env OCTAGON_API_KEY=your_octagon_api_key npx -y octagon-deep-research-mcp

Manual Installation

npm install -g octagon-deep-research-mcp

Documentation

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:

  • Detailed API references

  • Research methodology guidelines

  • Examples and use cases

  • Best practices for comprehensive research

  • Advanced features and capabilities

Available Tool

octagon-deep-research-agent

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.

๐Ÿ“š Example Research Queries

Technology & AI Research

  • "Research the current state of quantum computing development and commercial applications across major tech companies"

  • "Analyze the competitive landscape in large language models, comparing capabilities, limitations, and market positioning"

  • "Investigate recent developments in autonomous vehicle technology and regulatory challenges"

  • "Study the evolution of edge computing architectures and their impact on IoT deployment"

Healthcare & Medical Research

  • "Research breakthrough medical treatments for Alzheimer's disease developed in the last 3 years"

  • "Analyze the effectiveness of different COVID-19 vaccine technologies and their global distribution"

  • "Investigate the current state of gene therapy research for rare diseases"

  • "Study mental health treatment innovations and their accessibility across different demographics"

Environmental & Sustainability

  • "Research sustainable agriculture practices and their adoption rates globally"

  • "Analyze renewable energy adoption trends and policy drivers across different countries"

  • "Investigate the environmental impact of cryptocurrency mining and proposed solutions"

  • "Study carbon capture technologies and their commercial viability"

Business & Economics

  • "Analyze the gig economy's impact on traditional employment models and worker protections"

  • "Research the evolution of remote work policies post-pandemic and their effectiveness on productivity"

  • "Investigate supply chain resilience strategies adopted after global disruptions"

  • "Study the impact of digital transformation on traditional retail businesses"

Social & Cultural Studies

  • "Research the impact of social media algorithms on information consumption patterns and political polarization"

  • "Analyze changing demographics in urban areas and their impact on city planning"

  • "Investigate the effectiveness of different approaches to digital literacy education"

  • "Study the cultural impact of streaming services on traditional media consumption"

Science & Engineering

  • "Research advances in materials science for semiconductor manufacturing"

  • "Analyze the development of fusion energy technologies and timeline to commercialization"

  • "Investigate innovations in water purification technologies for developing regions"

  • "Study the engineering challenges and solutions for space exploration missions"

Policy & Governance

  • "Investigate recent developments in AI regulation across different countries and their potential impact"

  • "Research privacy legislation trends and their effects on technology companies"

  • "Analyze different approaches to cryptocurrency regulation globally"

  • "Study the effectiveness of various climate policy mechanisms"

Cybersecurity & Privacy

  • "Investigate cybersecurity threats in IoT devices and enterprise mitigation strategies"

  • "Research the evolution of ransomware attacks and defensive technologies"

  • "Analyze privacy-preserving technologies and their adoption in consumer applications"

  • "Study the security implications of quantum computing on current encryption methods"

Education & Learning

  • "Research the effectiveness of different online learning platforms and methodologies"

  • "Analyze the impact of AI tools on academic research and education"

  • "Investigate innovative approaches to STEM education in underserved communities"

  • "Study the future of skills-based learning and certification programs"

๐Ÿ” Research Capabilities

  • Multi-Source Analysis: Aggregates information from academic papers, industry reports, news sources, and expert opinions

  • Real-Time Data: Accesses current information and recent developments

  • Cross-Verification: Validates findings across multiple reliable sources

  • Trend Analysis: Identifies patterns and forecasts future developments

  • Competitive Intelligence: Comprehensive competitive landscape analysis

  • Technical Deep-Dives: Detailed analysis of complex technical topics

  • Policy Impact Assessment: Analysis of regulatory and policy implications

  • Market Dynamics: Understanding of market forces and business implications

Troubleshooting

  1. API Key Issues: Ensure your Octagon API key is correctly set in the environment or config file.

  2. Connection Issues: Make sure the connectivity to the Octagon API is working properly.

  3. Rate Limiting: No rate limits apply to Deep Research MCP - execute unlimited queries.

License

MIT


โญ Star this repo if you find it helpful for your research needs!

Available Tools

1 tool
octagon-deep-research-agentB

A specialized agent for deep research and comprehensive analysis across any topic or domain. Capabilities: Multi-source data aggregation, web scraping, academic research synthesis, competitive analysis, market intelligence, technical analysis, policy research, trend analysis, and comprehensive report generation. Best for: Any research question requiring comprehensive, multi-source analysis and synthesis. Example queries: 'Research the current state of quantum computing development and commercial applications', 'Analyze the competitive landscape in the electric vehicle market focusing on battery technology and supply chains', 'Investigate recent developments in AI regulation across different countries and their potential impact', 'Research sustainable agriculture practices and their adoption rates globally', 'Analyze the gig economy's impact on traditional employment models', 'Study the evolution of remote work policies post-pandemic and their effectiveness', 'Research breakthrough medical treatments for Alzheimer's disease in the last 3 years', 'Investigate cybersecurity threats in IoT devices and mitigation strategies', 'Analyze renewable energy adoption trends and policy drivers worldwide', 'Research the impact of social media algorithms on information consumption patterns'.

ParametersJSON Schema
NameRequiredDescriptionDefault
promptYesYour natural language query or request for the agent

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it lists capabilities (e.g., web scraping, synthesis), it doesn't disclose critical behavioral traits such as execution time, rate limits, authentication requirements, data sources used, or output format. The description implies complex operations but lacks transparency about how they work.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is overly verbose and poorly structured. It front-loads the purpose but then includes a lengthy, repetitive list of capabilities and 10 example queries that could be condensed. Many sentences don't earn their place, making it inefficient for quick comprehension by an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's apparent complexity (deep research with multiple capabilities), no annotations, and no output schema, the description is incomplete. It fails to address critical contextual elements like what the output looks like, execution limitations, error handling, or data source reliability, leaving significant gaps for an agent to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the single parameter 'prompt' clearly documented as 'Your natural language query or request for the agent'. The description doesn't add meaningful semantic context beyond what the schema provides, such as formatting examples or constraints, so it meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'deep research and comprehensive analysis across any topic or domain' and lists specific capabilities like multi-source data aggregation, web scraping, and report generation. However, it doesn't distinguish from sibling tools (none provided), so it cannot achieve a perfect score for sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('Best for: Any research question requiring comprehensive, multi-source analysis and synthesis') and includes 10 detailed example queries that illustrate appropriate use cases. It lacks explicit exclusions or alternatives, but with no sibling tools, this is less critical.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedoctagon-deep-research-agent

TDQS

B3.2/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'octagon-deep-research-agent' has a clearly defined and distinct purpose focused on comprehensive research and analysis.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'octagon-deep-research-agent' follows a clear, descriptive pattern that aligns with the server's purpose.

Tool Count2/5

A single tool is generally too few for a server claiming to handle 'deep research across any topic or domain,' as this suggests a broad scope requiring multiple specialized operations. While the tool is comprehensive, the lack of modularity (e.g., separate tools for data aggregation, synthesis, or report generation) limits flexibility and indicates an under-scoped surface for the apparent domain.

Completeness2/5

The tool surface is severely incomplete for a research domain. There are no distinct tools for key operations like querying specific sources, managing research workflows, updating analyses, or generating different report formats. The single tool attempts to cover everything, but this monolithic approach creates gaps in modular control and likely leads to agent failures when precise, step-by-step operations are needed.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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