deepwiki-mcp
deepwiki-mcp is hosted online, so all tools can be tested directly either in theInspector tabor in theOnline Client.
If you are the rightful owner of deepwiki-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
This is an unofficial Deepwiki MCP Server that processes Deepwiki URLs, crawls pages, converts them to Markdown, and returns documents or lists by page.
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"]
}
}
}
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 repositorymode
(optional): Output mode, either "aggregate" for a single Markdown document (default) or "pages" for structured page datamaxDepth
(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/deepwiki-mcp.git
cd deepwiki-mcp
# 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
-
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
-
Connection Refused: Make sure the port is available and not blocked by a firewall:
# Check if port is in use lsof -i :3000
-
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 for details.
License
MIT
Links
- X/Twitter: @kregenrek
- Bluesky: @kevinkern.dev
Courses
- Learn Cursor AI: Ultimate Cursor Course
- Learn to build software with AI: instructa.ai
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