Python web scraping toolkit and MCP server that gives AI agents clean, structured web data from any URL or built-in scrapers.
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PyScrappy is an MCP server that python web scraping toolkit and MCP server that gives AI agents clean, structured web data from any URL or built-in scrapers. Its tool list has not been published yet over stdio and http, requires no API key, and scores 63/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"pyscrappy": {
"command": "pyscrappy-mcp"
}
}
}Are you the author?
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PyScrappy is a Python toolkit for web scraping that works out of the box. Point it at any URL and get structured data back — or use built-in scrapers for Wikipedia, IMDB, Yahoo Finance, news feeds, and more.
This server supports HTTP transport. Be the first to test it — help the community know if it works.
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No known CVEs.
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PyScrappy is an AI-native web scraping toolkit that turns websites into structured, LLM-ready data. Use it as a Python library or expose it as an MCP server for AI agents.
📖 Documentation: pyscrappy.vercel.app
.to_markdown() turns any result into clean Markdown; also .to_json() and .to_dataframe()Selector — navigate HTML directly with CSS/XPath, find_all, find_by_text, and find_similar (Scrapy/BeautifulSoup-style)scrape_many / scrape_all run scrapes in parallelimpersonate="chrome" gets past anti-bot filters that block plain clients (optional curl_cffi backend)pyscrappy extract <url> out.md scrapes a URL straight to a file, no codepy.typed markerpip install pyscrappy
Optional extras:
# Browser support (for JS-rendered pages)
pip install 'pyscrappy[browser]'
playwright install chromium
# DataFrame support
pip install 'pyscrappy[dataframe]'
# MCP server (use PyScrappy's scrapers as AI-agent tools)
pip install 'pyscrappy[mcp]'
# Stealth (TLS-fingerprint impersonation to bypass anti-bot filters)
pip install 'pyscrappy[stealth]'
# Everything
pip install 'pyscrappy[all]'
PyScrappy ships an MCP server that exposes its scrapers as tools, so an agent (Claude, Cursor, an OpenAI agent, a local LLM) can pull structured web data from any URL and hand it straight to the model:
AI agent ──MCP tool call──▶ PyScrappy ──fetch + extract──▶ Any website
▲ │
└────────────── clean Markdown / JSON ◀───────────────────────┘
pip install 'pyscrappy[mcp]'
claude mcp add pyscrappy pyscrappy-mcp
Then just ask: "use pyscrappy to summarize the latest headlines from bbc.com." See [MCP server](