Easily retrieve swift language documentation from GitHub, NPM, PyPI, and web pages with accurate, up-to-date references
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
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
Unblocked
Bring full context to every agent and AI tools
JupiterOne
Ask questions about your JupiterOne agentic security and it asset graph and manage alerts, rules, and dashboards — in natural language.
Elastic Cloud Serverless
Search, Observe, and Protect your Elasticsearch Data
YouTrack
Plan and track work in YouTrack
Sprites
Let Claude manage your Sprites
Subtext
Session replay, built for agents. Give Claude a session link and it investigates the real production session—DOM, screenshots, console, network—to find the root cause.
Useful MCP listing: Documentation Scraper is the kind of server we cite when onboarding engineers to host + tool permissions.
Strong directory entry: Documentation Scraper surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Documentation Scraper is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We wired Documentation Scraper into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Documentation Scraper reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Documentation Scraper is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Documentation Scraper is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Documentation Scraper is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated Documentation Scraper against two servers with overlapping tools; this profile had the clearer scope statement.
Documentation Scraper is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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Share your MCP server with the developer community
Select a client to integrate this server.
Claude Desktop configuration
{
"mcpServers": {
"docs-mcp-server": {
"command": "npx",
"args": [
"-y",
"@arabold/docs-mcp-server@latest"
]
}
}
}Fetches and indexes official documentation from GitHub, NPM, PyPI, and web sources so AI assistants can reference current, accurate library docs instead of hallucinating outdated information.
Documentation Scraper is a community-built MCP server published by arabold that provides AI assistants with tools and capabilities via the Model Context Protocol. Easily retrieve swift language documentation from GitHub, NPM, PyPI, and web pages with accurate, up-to-date references It is categorized under search web, developer tools.
You can install Documentation Scraper 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 runs locally on your machine via the stdio transport.
Docs MCP Server solves the problem of AI hallucinations and outdated knowledge by providing a personal, always-current documentation index for your AI coding assistant. It fetches official docs from websites, GitHub, npm, PyPI, and local files, allowing your AI to query the exact version you are using.
The open-source alternative to Context7, Nia, and Ref.Tools.
1. Start the server (requires Node.js 22+):
npx @arabold/docs-mcp-server@latest
2. Open the Web UI at http://localhost:6280 to add documentation.
3. Connect your AI client by adding this to your MCP settings (e.g., claude_desktop_config.json):
{
"mcpServers": {
"docs-mcp-server": {
"type": "sse",
"url": "http://localhost:6280/sse"
}
}
}
See Connecting Clients for VS Code (Cline, Roo) and other setup options.
<details> <summary>Alternative: Run with Docker</summary>docker run --rm \
-v docs-mcp-data:/data \
-v docs-mcp-config:/config \
-p 6280:6280 \
ghcr.io/arabold/docs-mcp-server:latest \
--protocol http --host 0.0.0.0 --port 6280
Using an embedding model is optional but dramatically improves search quality by enabling semantic vector search.
Example: Enable OpenAI Embeddings
OPENAI_API_KEY="sk-proj-..." npx @arabold/docs-mcp-server@latest
See Embedding Models for configuring Ollama, Gemini, Azure, and others.
We welcome contributions! Please see CONTRIBUTING.md for development guidelines and setup instructions.
This project is licensed under the MIT License. See LICENSE for details.
Time estimate: 20-40 minutes including configuration and testing
Prerequisites
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.