Octocode MCP

Octocode MCP

Enterprise-grade AI context server for codebase research and analysis.

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Octocode MCP is a Model Context Protocol (MCP) server designed to enable AI assistants to search, analyze, and extract insights from millions of GitHub repositories with high security and token efficiency. It offers intelligent orchestration for deep code research, planning, and agentic workflows, streamlining the process of building and understanding complex software projects. The platform features robust tools and commands, such as /research for expert code research, designed to support developers and AI systems with context-rich information.

Key Features

Implements Model Context Protocol (MCP)
Enterprise-grade security for data handling
Token-efficient context management
Automated deep code research
Contextual insights extraction from repositories
Expert research and planning commands
/research command for comprehensive code investigation
Integration with GitHub for large-scale repository analysis
Support for agentic workflows and AI orchestration
User-facing documentation and tutorials

Use Cases

Automating deep research on open-source codebases
Assisting AI agents with context-aware code analysis
Extracting architectural and implementation plans from repositories
Building full-stack applications via automated code research
Enhancing AI assistants with secure access to repository insights
Token-efficient management of large codebase contexts
Developing custom research agents for software projects
Facilitating continuous integration of recent code trends and patterns
Supporting enterprise workflows involving code scrutiny and planning
Providing tools for real-time codebase queries and insights

README

GitHub Stats

A Model Context Protocol (MCP) server enabling AI assistants to search, analyze, and extract insights from millions of GitHub repositories with enterprise-grade security and token efficiency.

MCP Community Server Ask DeepWiki Trust Score

Website – Official site

YouTube Channel – Video tutorials and examples


Table of Contents


See It In Action

Full-Stack Application Built in Under 10 Minutes

Watch AI assistant use Octocode to research, plan, and build a complete chat application with Express backend.

Prompt:

Use Octocode MCP for Deep Research

I want to build an application with chat (front-end) that shows a chat window to the user. The user enters a prompt in the chat, and the application sends the prompt to an Express backend that uses AI to process the request.

Add a return box (to show the message returned from the AI) and loaders to the UI. I want to build an AI agent system in Node.js using LangChain and LangGraph. Can you research the latest patterns?

Please conduct thorough research on how to create this in the best way possible. Focus on repositories with good documentation and recent activity.

  • Do a deep research
  • Create a plan document
  • Initiate the plan and create the application

Phase 1: Research & Planning

https://github.com/user-attachments/assets/4225ab98-ae2f-46dc-b3ce-7d117e552b8c

Octocode Plan Document - Detailed architecture and step-by-step guide

Phase 2: Implementation

https://github.com/user-attachments/assets/2aaee9f1-3592-438a-a633-255b5cbbb8e1

Result: Production-ready full-stack application with authentication, real-time features, and best practices - All in less than 10 minutes


Research and Build Fullstack Agentic Application with /research command in Under 10 Minutes

Why use the /research command? Instead of manually searching through repositories and piecing together information, let the AI conduct comprehensive research for you:

  • 🎯 Intelligent Tool Orchestration: Automatically selects and combines the right Octocode tools (repository search, code search, file content, PR analysis, repo structure) based on your research needs
  • 🧠 Smart Decision Making: Makes strategic choices throughout the research flow—when to search broadly vs. specifically, which repositories to explore, and how to validate findings
  • 👥 Multi-Purpose Research: Perfect for feature discovery (product managers), code understanding (developers), bug investigation, flow analysis, planning from scratch, dependency tracking, security audits, and more
  • 🔬 Specialized Workflows: Handles Technical Research (code flows), Product Research (docs+code validation), Pattern Analysis (cross-repo comparison), Bug Investigation, Architecture Mapping, API Research, Security/Auth flows, and more
  • 🔍 Transparent Reasoning: Shows you exactly which tools it's using, what it's searching for, and why at each step
  • 🎨 Adaptive Strategy: Works across public repos, private organizations, and specific repositories with configurable depth (overview, deep dive, or cross-repo comparison)
  • 📊 Cross-Validated Results: Leverages multiple Octocode tools to verify information from different sources and perspectives
  • 🚀 Actionable Insights: Delivers implementation-ready plans with code examples, not just raw information

Prompt:

/octocode/research How can I use LangChain, LangGraph, and similar open-source AI tools to create agentic flows between agents for goal-oriented tasks? Can you suggest UI frameworks I can use to build a full-stack AI application?

https://github.com/user-attachments/assets/82ed97ae-57a9-46ae-9acd-828a509e711b


Discover APIs, Frameworks, and Dive Into Internal Implementation Details

Octocode excels at both broad discovery and deep code analysis. Whether you're exploring new APIs, finding frameworks, or understanding how popular libraries work under the hood, Octocode provides comprehensive answers in seconds.

First Prompt - Broad Discovery:

list top repositories for:

  • Stock market APIs (Typescript)
  • Cursor rules examples
  • UI for AI
  • Mobile development using React
  • State management for React

What happens: Octocode searches across GitHub to find the most popular and well-maintained repositories for each category, analyzing stars, activity, documentation quality, and recent updates. You get curated lists with context about each repository's strengths.

Second Prompt - Deep Implementation Analysis:

How React implemented useState under the hood?

What happens: Octocode dives into React's source code, traces the implementation flow, analyzes the relevant files (ReactHooks.js, ReactFiberHooks.js), and explains the internal mechanics including fiber architecture, hook state management, and dispatcher patterns—all with code references and detailed explanations.

The Power: Move seamlessly from discovering what exists to understanding how it works in a single conversation. No manual repository hunting or code spelunking required.

https://github.com/user-attachments/assets/c184d5d4-c9b6-40a1-a55a-41cb9b3ecc4f


Installation

Prerequisites

  • Node.js >= 18.12.0
  • GitHub Authentication (choose one):

Getting started

First, install the Octocode MCP server with your client.

Standard config works in most of the tools:

js
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": [
        "octocode-mcp@latest"
      ]
    }
  }
}

Note: This configuration uses GitHub CLI authentication. For Personal Access Token, see the Authentication Guide below.

Add via the Amp VS Code extension settings screen or by updating your settings.json file:

json
"amp.mcpServers": {
  "octocode": {
    "command": "npx",
    "args": [
      "octocode-mcp@latest"
    ]
  }
}

Amp CLI Setup:

Add via the amp mcp add command below:

bash
amp mcp add octocode -- npx octocode-mcp@latest

Use the Claude Code CLI to add the Octocode MCP server:

bash
claude mcp add octocode npx octocode-mcp@latest

Follow the MCP install guide, use the standard config above.

Use the Codex CLI to add the Octocode MCP server:

bash
codex mcp add octocode npx "octocode-mcp@latest"

Alternatively, create or edit the configuration file ~/.codex/config.toml and add:

toml
[mcp_servers.octocode]
command = "npx"
args = ["octocode-mcp@latest"]

For more information, see the Codex MCP documentation.

Click the button to install:

Or install manually:

Go to Cursor Settings -> MCP -> Add new MCP Server. Name to your liking, use command type with the command npx octocode-mcp@latest. You can also verify config or add command like arguments via clicking Edit.

Project-Specific Configuration

Create .cursor/mcp.json in your project root:

json
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": ["octocode-mcp@latest"]
    }
  }
}

Add via the Cline VS Code extension settings or by updating your cline_mcp_settings.json file:

json
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": [
        "octocode-mcp@latest"
      ]
    }
  }
}

Follow the MCP install guide, use the standard config above.

Click the button to install:

Install in Goose

Or install manually:

Go to Advanced settings -> Extensions -> Add custom extension. Name to your liking, use type STDIO, and set the command to npx octocode-mcp@latest. Click "Add Extension".

Follow the MCP Servers documentation. For example in .kiro/settings/mcp.json:

json
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": [
        "octocode-mcp@latest"
      ]
    }
  }
}

Click the button to install:

Add MCP Server octocode to LM Studio

Or install manually:

Go to Program in the right sidebar -> Install -> Edit mcp.json. Use the standard config above.

Follow the MCP Servers documentation. For example in ~/.config/opencode/opencode.json:

json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "octocode": {
      "type": "local",
      "command": [
        "npx",
        "octocode-mcp@latest"
      ],
      "enabled": true
    }
  }
}

Open Qodo Gen chat panel in VSCode or IntelliJ → Connect more tools → + Add new MCP → Paste the standard config above.

Click Save.

Click the button to install:

Or install manually:

Follow the MCP install guide, use the standard config above. You can also install the Octocode MCP server using the VS Code CLI:

bash
# For VS Code
code --add-mcp '{"name":"octocode","command":"npx","args":["octocode-mcp@latest"]}'

After installation, the Octocode MCP server will be available for use with your GitHub Copilot agent in VS Code.

Go to Settings -> AI -> Manage MCP Servers -> + Add to add an MCP Server. Use the standard config above.

Alternatively, use the slash command /add-mcp in the Warp prompt and paste the standard config from above:

js
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": [
        "octocode-mcp@latest"
      ]
    }
  }
}

Follow Windsurf MCP documentation. Use the standard config above.

Follow the MCP Servers documentation. Use the standard config above.


Authentication Methods

Octocode MCP supports two authentication methods:

Option 1: GitHub CLI (Recommended)

Advantages: Automatic token management, works with 2FA, supports SSO

bash
# Install GitHub CLI
# macOS
brew install gh

# Windows
winget install --id GitHub.cli

# Linux
# See https://github.com/cli/cli/blob/trunk/docs/install_linux.md

# Authenticate
gh auth login

Then use the standard configuration (no GITHUB_TOKEN needed).

Option 2: Personal Access Token

When to use: CI/CD environments, automation, or if GitHub CLI isn't available

  1. Create a token at github.com/settings/tokens
  2. Select scopes: repo, read:user, read:org
  3. Add to your MCP configuration:
json
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": ["octocode-mcp@latest"],
      "env": {
        "GITHUB_TOKEN": "ghp_your_token_here"
      }
    }
  }
}

Security Tip: Never commit tokens to version control. Use environment variables or secure secret management.


Verify Installation

After installation, verify Octocode MCP is working:

  1. Restart your MCP client completely
  2. Check connection status:
    • Cursor: Look for green dot in Settings → Tools & Integrations → MCP Tools
    • Claude Desktop: Check for "octocode" in available tools
    • VS Code: Verify in GitHub Copilot settings
  3. Test with a simple query:
    Search GitHub for React hooks implementations
    

If you see Octocode tools being used, you're all set! 🎉


GitHub Enterprise Support

Octocode MCP supports GitHub Enterprise Server instances with custom API URLs.

Configuration

Add the GITHUB_API_URL environment variable to your MCP configuration:

json
{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": ["octocode-mcp@latest"],
      "env": {
        "GITHUB_TOKEN": "your_token",
        "GITHUB_API_URL": "https://github.company.com/api/v3"
      }
    }
  }
}

Default: If not specified, defaults to https://api.github.com (public GitHub).

Note: Ensure your GitHub Enterprise token has the same scopes as documented in the Authentication Guide.


More Examples

Additional Demonstrations

ThreeJS Implementation Quality Comparison

Interactive Demo

Side-by-side comparison showing:

  • Generic AI: Basic implementation with common patterns
  • Octocode-Enhanced AI: Production-grade implementation with advanced techniques from real projects

Key Differences:

  • Performance optimizations from high-performance projects
  • Proper resource management patterns
  • Industry-standard error handling
  • Real-world edge case handling

Deep Technical Research

YouTube: React Hooks Internals

Demonstrates progressive research workflow:

  1. Repository discovery (React source)
  2. Structure exploration (hooks implementation)
  3. Code analysis (internal mechanisms)
  4. Comprehensive explanation with code references

Overview

Octocode is an agentic code research platform that bridges the gap between AI assistants and real-world code implementations. By providing structured access to GitHub's vast repository ecosystem, it enables AI systems to learn from production codebases rather than relying solely on training data.

Core Capabilities

Capability Implementation Benefit
Code Discovery Multi-dimensional search across repositories, code, and pull requests Find relevant implementations in seconds
Context Extraction Smart content retrieval with pattern matching and line-range targeting Get exactly the context you need
Token Optimization Advanced minification strategies (50+ language support) 30-70% reduction in token consumption
Security Automatic secrets detection and content sanitization Enterprise-grade data protection
Progressive Research Workflow-driven exploration (Discover → Explore → Analyze) Deep understanding of complex systems
Access Control GitHub permission-based access to public and private repositories Organization-wide code research

Tools

Octocode provides five specialized research tools designed to work together for comprehensive code analysis:

🔍 githubSearchCode

Find code implementations across repositories

Search for specific code patterns, functions, or implementations across millions of repositories.

Key Features:

  • Content Search: Find code inside files by keywords (AND logic)
  • Path Search: Discover files/directories by name (25x faster)
  • Smart Filtering: Scope by repository, path, file extension, or popularity
  • Context-Rich Results: Returns code snippets with surrounding context

Common Use Cases:

• Find implementation examples: "How do popular repos implement OAuth?"
• Discover patterns: "Search for React custom hooks in vercel repos"
• Locate functions: "Find error handling patterns in Express apps"

📚 githubSearchRepositories

Discover repositories by topics and keywords

Your starting point for repository discovery - find the right projects to analyze.

Key Features:

  • Topic-Based Discovery: Search by exact GitHub topics (most precise)
  • Keyword Search: Find repos by name, description, or README content
  • Quality Filters: Filter by stars, language, size, activity
  • Sorting Options: By popularity, recency, or relevance

Common Use Cases:

• Find popular implementations: "Discover TypeScript CLI tools with >1000 stars"
• Research ecosystems: "Find all React state management libraries"
• Organization research: "List all repos from microsoft with topic 'ai'"

🗂️ githubViewRepoStructure

Explore repository directory structure

Understand how a project is organized before diving into specific files.

Key Features:

  • Directory Tree: Visual representation of folder structure
  • File Sizes: See file sizes to identify important components
  • Depth Control: Explore 1 level (overview) or 2 levels (detailed)
  • Path Targeting: Navigate directly to specific directories

Common Use Cases:

• Project overview: "Show me the structure of facebook/react"
• Find entry points: "Explore src/ directory in a monorepo"
• Understand architecture: "Navigate to the API implementation folder"

📄 githubGetFileContent

Read file contents with smart extraction

Retrieve specific content from files efficiently - full files or targeted sections.

Key Features:

  • Pattern Matching: Extract sections matching specific patterns with context
  • Line Range Reading: Read specific line ranges for efficiency
  • Full Content Access: Get entire file when needed
  • Content Minification: Automatic optimization for token efficiency

Common Use Cases:

• Read specific functions: "Get the validateUser function from auth.ts"
• Extract sections: "Show me all the middleware definitions in app.js"
• Read configuration: "Get the full package.json file"
• Analyze specific code: "Read lines 100-150 from the API handler"

🔀 githubSearchPullRequests

Analyze pull requests, changes, and discussions

Understand how code evolved, why decisions were made, and learn from production changes.

Key Features:

  • PR Discovery: Search by state, author, labels, dates
  • Direct Access: Fetch specific PR by number (10x faster)
  • Code Diffs: Include full diff content to see what changed
  • Discussions: Access comment threads and review discussions
  • Merged Code: Filter for production-ready, merged changes

Common Use Cases:

• Learn from changes: "Show recent merged PRs about authentication"
• Understand decisions: "Find PRs discussing the API redesign with comments"
• Track implementations: "See how feature X was implemented with diffs"
• Expert contributions: "Find PRs by @author in the last 6 months"

Full Documentation →


Commands

Octocode MCP provides intelligent prompt commands that enhance your research workflow:

/research - Expert Code Research Agent

Purpose: Systematic code research using decision-tree workflows

When to use:

  • Understanding repository workflows: Discover how repositories work, trace specific flows through codebases, and understand technical implementations
  • Cross-repository flow analysis: Understand complex flows that span multiple repositories, trace data flows across microservices, or analyze how different repos interact
  • Technical flow investigation: Deep-dive into technical flows within or across repositories (even cross-repo dependencies and integrations)
  • Real-world code examples: Learn from actual production code implementations, not just documentation or tutorials
  • Deep technical investigations: Trace code flows, understand complex implementations, analyze architecture decisions
  • Answering team questions: Quickly research Slack/Jira questions about features, APIs, or behavior with code-backed answers
  • Bug investigation: Find root causes by analyzing code, commit history, and related PRs
  • Organization features: Understand how features work across your private/public repositories
  • Pattern discovery: Compare implementations across multiple repos to find best practices
  • Documentation validation: Verify docs match actual code behavior

What it does:

  • Provides systematic guidance through research stages (discovery → exploration → analysis → synthesis)
  • Executes multiple queries in parallel for faster results
  • Shows transparent reasoning at each step
  • Adapts to different research types: code implementation, documentation validation, pattern comparison, or bug investigation

Usage Examples (by research type):

Technical Research (code-first, understanding implementations):

/research How does React's useState hook work internally?
/research How to build a LangChain application with Express backend and Next.js frontend?

Product Research (docs + code validation):

/research What are the rate limiting features in our API according to docs and actual code?
/research How does authentication work in NextAuth.js? Verify docs against implementation

Pattern Analysis (comparing multiple implementations):

/research Compare state management approaches: Redux vs Zustand vs Jotai
/research How do popular repos handle WebSocket reconnection logic?

Bug Investigation (root cause analysis):

/research Why is the payment webhook failing? Trace the error through payment-service
/research User reports slow dashboard loading - investigate performance issues in myorg/frontend

Key Features:

  • Progressive refinement (broad → specific → deep dive)
  • Code-as-truth validation (verifies docs against actual implementation)
  • Cross-repository pattern analysis (public & private repos)
  • Comprehensive synthesis with Mermaid diagrams and cited references
  • Perfect for answering technical questions from Slack/Jira with code evidence

/kudos - Repository Appreciation

Purpose: List and appreciate all GitHub repositories used in your research session

When to use:

  • End of a research session to see what repos helped you
  • Finding repositories to star and support

What it does:

  • Analyzes conversation history
  • Identifies all GitHub repositories explored via Octocode tools
  • Creates formatted list with links and usage notes
  • Reminds you to show appreciation to maintainers

Usage:

/kudos

Output Example:

markdown
# Repositories Used in This Research

## ⭐ Repositories Explored

1. **facebook/react** — https://github.com/facebook/react
   Searched for hooks implementation and internals

2. **vercel/next.js** — https://github.com/vercel/next.js
   Explored routing architecture

/use - Quick Reference Guide

Purpose: Simple reminder of Octocode MCP capabilities and best practices

When to use:

  • Quick refresher on available tools
  • Learning key practices for efficient research
  • Getting started with Octocode

What it covers:

  • Code Discovery: Search repositories, explore structures, find patterns
  • Deep Analysis: Read files, analyze PRs with diffs, track commits
  • Research Workflow: Progressive refinement methodology
  • Key Practices: Bulk queries, partial file access, search-first approach

Usage:

/use

Tips for Using Commands

  1. Start with /use if you're new to Octocode MCP
  2. Use /research for all code research - This is the recommended way to use Octocode for any research task, providing structured guidance and optimal tool usage
  3. Run /kudos at the end of sessions to document sources and show appreciation
  4. Commands work in any MCP-compatible client (Claude, Cursor, etc.)

💡 Pro Tip: For any code research, start with /research in Octocode MCP. This command intelligently orchestrates all tools for you, optimizing your workflow, depth of analysis, and research quality.


Documentation

Comprehensive Guides

Resource Description Link
Configuration Guide Environment variables and server configuration CONFIGURATION.md
Authentication Guide Setup instructions and troubleshooting AUTH_GUIDE.md

Community

Get Support

Show Your Support

If Octocode helps your AI development workflow:

  • Star the repository on GitHub
  • Share on social media with #OctocodeMCP

License

MIT - See LICENSE for details.

Star History

Star History Chart

Repository Owner

bgauryy
bgauryy

User

Repository Details

Language TypeScript
Default Branch main
Size 106,140 KB
Contributors 5
License MIT License
MCP Verified Nov 12, 2025

Programming Languages

TypeScript
99.72%
JavaScript
0.18%
Dockerfile
0.1%

Tags

Topics

agent ai ai-agents ai-tools claude-ai code-intelligence code-search context cursor cursor-ai development github github-api llm mcp model-context-protocol modelcontextprotocol octocode semantic-search vibe-coding

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