Sponsored by Deepsite.site

Deepwiki MCP Server

Created By
instructa7 months ago
A MCP Server that gives you latest docs and data from the web
Content

Deepwiki MCP Server

This is an unofficial Deepwiki MCP Server

It takes a Deepwiki URL via MCP, crawls all relevant pages, converts them to Markdown, and returns either one document or a list by page.

Features

  • 🔒 Domain Safety: Only processes URLs from deepwiki.com
  • 🧹 HTML Sanitization: Strips headers, footers, navigation, scripts, and ads
  • 🔗 Link Rewriting: Adjusts links to work in Markdown
  • 📄 Multiple Output Formats: Get one document or structured pages
  • 🚀 Performance: Fast crawling with adjustable concurrency and depth
  • NLP: It's to search just for the library name

Usage

Prompts you can use:

deepwiki fetch how can i use gpt-image-1 with "vercel ai" sdk
deepwiki fetch how can i create new blocks in shadcn?
deepwiki fetch i want to understand how X works

Fetch complete Documentation (Default)

use deepwiki https://deepwiki.com/shadcn-ui/ui
use deepwiki multiple pages https://deepwiki.com/shadcn-ui/ui

Single Page

use deepwiki fetch single page https://deepwiki.com/tailwindlabs/tailwindcss/2.2-theme-system

Get by shortform

use deepwiki fetch tailwindlabs/tailwindcss
deepwiki fetch library

deepwiki fetch url
deepwiki fetch <name>/<repo>

deepwiki multiple pages ...
deepwiki single page url ...

Cursor

Add this to .cursor/mcp.json file.

{
  "mcpServers": {
    "mcp-deepwiki": {
      "command": "npx",
      "args": ["-y", "mcp-deepwiki@latest"]
    }
  }
}

Deepwiki Logo

MCP Tool Integration

The package registers a tool named deepwiki_fetch that you can use with any MCP-compatible client:

{
  "action": "deepwiki_fetch",
  "params": {
    "url": "https://deepwiki.com/user/repo",
    "mode": "aggregate",
    "maxDepth": "1"
  }
}

Parameters

  • url (required): The starting URL of the Deepwiki repository
  • mode (optional): Output mode, either "aggregate" for a single Markdown document (default) or "pages" for structured page data
  • maxDepth (optional): Maximum depth of pages to crawl (default: 10)

Response Format

Success Response (Aggregate Mode)

{
  "status": "ok",
  "data": "# Page Title\n\nPage content...\n\n---\n\n# Another Page\n\nMore content...",
  "totalPages": 5,
  "totalBytes": 25000,
  "elapsedMs": 1200
}

Success Response (Pages Mode)

{
  "status": "ok",
  "data": [
    {
      "path": "index",
      "markdown": "# Home Page\n\nWelcome to the repository."
    },
    {
      "path": "section/page1",
      "markdown": "# First Page\n\nThis is the first page content."
    }
  ],
  "totalPages": 2,
  "totalBytes": 12000,
  "elapsedMs": 800
}

Error Response

{
  "status": "error",
  "code": "DOMAIN_NOT_ALLOWED",
  "message": "Only deepwiki.com domains are allowed"
}

Partial Success Response

{
  "status": "partial",
  "data": "# Page Title\n\nPage content...",
  "errors": [
    {
      "url": "https://deepwiki.com/user/repo/page2",
      "reason": "HTTP error: 404"
    }
  ],
  "totalPages": 1,
  "totalBytes": 5000,
  "elapsedMs": 950
}

Progress Events

When using the tool, you'll receive progress events during crawling:

Fetched https://deepwiki.com/user/repo: 12500 bytes in 450ms (status: 200)
Fetched https://deepwiki.com/user/repo/page1: 8750 bytes in 320ms (status: 200)
Fetched https://deepwiki.com/user/repo/page2: 6200 bytes in 280ms (status: 200)

Local Development - Installation

Local Usage

{
  "mcpServers": {
    "mcp-deepwiki": {
      "command": "node",
      "args": ["./bin/cli.mjs"]
    }
  }
}

From Source

# Clone the repository
git clone https://github.com/regenrek/mcp-deepwiki.git
cd mcp-deepwiki

# Install dependencies
npm install

# Build the package
npm run build

Direct API Calls

For HTTP transport, you can make direct API calls:

curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "id": "req-1",
    "action": "deepwiki_fetch",
    "params": {
      "url": "https://deepwiki.com/user/repo",
      "mode": "aggregate"
    }
  }'

Configuration

Environment Variables

  • DEEPWIKI_MAX_CONCURRENCY: Maximum concurrent requests (default: 5)
  • DEEPWIKI_REQUEST_TIMEOUT: Request timeout in milliseconds (default: 30000)
  • DEEPWIKI_MAX_RETRIES: Maximum retry attempts for failed requests (default: 3)
  • DEEPWIKI_RETRY_DELAY: Base delay for retry backoff in milliseconds (default: 250)

To configure these, create a .env file in the project root:

DEEPWIKI_MAX_CONCURRENCY=10
DEEPWIKI_REQUEST_TIMEOUT=60000
DEEPWIKI_MAX_RETRIES=5
DEEPWIKI_RETRY_DELAY=500

Docker Deployment (Untested)

Build and run the Docker image:

# Build the image
docker build -t mcp-deepwiki .

# Run with stdio transport (for development)
docker run -it --rm mcp-deepwiki

# Run with HTTP transport (for production)
docker run -d -p 3000:3000 mcp-deepwiki --http --port 3000

# Run with environment variables
docker run -d -p 3000:3000 \
  -e DEEPWIKI_MAX_CONCURRENCY=10 \
  -e DEEPWIKI_REQUEST_TIMEOUT=60000 \
  mcp-deepwiki --http --port 3000

Development

# Install dependencies
pnpm install

# Run in development mode with stdio
pnpm run dev-stdio

# Run tests
pnpm test

# Run linter
pnpm run lint

# Build the package
pnpm run build

Troubleshooting

Common Issues

  1. Permission Denied: If you get EACCES errors when running the CLI, make sure to make the binary executable:

    chmod +x ./node_modules/.bin/mcp-deepwiki
    
  2. Connection Refused: Make sure the port is available and not blocked by a firewall:

    # Check if port is in use
    lsof -i :3000
    
  3. Timeout Errors: For large repositories, consider increasing the timeout and concurrency:

    DEEPWIKI_REQUEST_TIMEOUT=60000 DEEPWIKI_MAX_CONCURRENCY=10 npx mcp-deepwiki
    

Contributing

We welcome contributions! Please see CONTRIBUTING.md for details.

License

MIT

Courses

See my other projects:

  • AI Prompts - Curated AI Prompts for Cursor AI, Cline, Windsurf and Github Copilot
  • codefetch - Turn code into Markdown for LLMs with one simple terminal command
  • aidex A CLI tool that provides detailed information about AI language models, helping developers choose the right model for their needs.# tool-starter
Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
WindsurfThe new purpose-built IDE to harness magic
DeepChatYour AI Partner on Desktop
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
TimeA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
Baidu Map百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
CursorThe AI Code Editor
Serper MCP ServerA Serper MCP Server
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code
Tavily Mcp
ChatWiseThe second fastest AI chatbot™
Howtocook Mcp基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server,帮你推荐菜谱、规划膳食,解决“今天吃什么“的世纪难题; Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
Amap Maps高德地图官方 MCP Server
Context7Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
Playwright McpPlaywright MCP server