by deepwiki
DeepWiki converts deepwiki.com pages into clean Markdown, with fast, secure extraction—perfect as a PDF text, page, or i
Connects AI assistants to GitHub repository documentation and provides search capabilities for understanding codebases and answering technical questions about projects.
DeepWiki is an official MCP server published by deepwiki that provides AI assistants with tools and capabilities via the Model Context Protocol. DeepWiki converts deepwiki.com pages into clean Markdown, with fast, secure extraction—perfect as a PDF text, page, or i It is categorized under search web.
You can install DeepWiki in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
MIT
DeepWiki is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Share your MCP server with the developer community
Useful MCP listing: DeepWiki is the kind of server we cite when onboarding engineers to host + tool permissions.
DeepWiki reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
DeepWiki is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend DeepWiki for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, DeepWiki benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
DeepWiki is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, DeepWiki benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired DeepWiki into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Useful MCP listing: DeepWiki is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated DeepWiki against two servers with overlapping tools; this profile had the clearer scope statement.
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⚠️ IMPORTANT NOTICE: This server is currently not working since DeepWiki has cut off the possibility to scrape it. We recommend using the official DeepWiki MCP server at https://docs.devin.ai/work-with-devin/deepwiki-mcp for the time being.
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.
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 ...
Add this to .cursor/mcp.json file.
{
"mcpServers": {
"mcp-deepwiki": {
"command": "npx",
"args": ["-y", "mcp-deepwiki@latest"]
}
}
}
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"
}
}
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){
"status": "ok",
"data": "# Page Title
Page content...
---
# Another Page
More content...",
"totalPages": 5,
"totalBytes": 25000,
"elapsedMs": 1200
}
{
"status": "ok",
"data": [
{
"path": "index",
"markdown": "# Home Page
Welcome to the repository."
},
{
"path": "section/page1",
"markdown": "# First Page
This is the first page content."
}
],
"totalPages": 2,
"totalBytes": 12000,
"elapsedMs": 800
}
{
"status": "error",
"code": "DOMAIN_NOT_ALLOWED",
"message": "Only deepwiki.com domains are allowed"
}
{
"status": "partial",
"data": "# Page Title
Page content...",
"errors": [
{
"url": "https://deepwiki.com/user/repo/page2",
"reason": "HTTP error: 404"
}
],
"totalPages": 1,
"totalBytes": 5000,
"elapsedMs": 950
}
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)
{
"mcpServers": {
"mcp-deepwiki": {
"command": "node",
"args": ["./bin/cli.mjs"]
}
}
}
# 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
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"
}
}'
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
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
# 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
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
We welcome contributions! Please see CONTRIBUTING.md for details.
MIT
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.