Scrapegraph-ai
Python scraper based on AI
Scrapegraph-ai MCP server enables AI-powered web scraping using large language models through the Model Context Protocol. This Python library creates intelligent scraping pipelines that extract structured data from websites and local documents (HTML, XML, JSON, Markdown) based on natural language prompts rather than rigid selectors. Developers can integrate it with Claude Desktop and other MCP-compatible clients to scrape content by simply describing the information they need. The server supports multiple LLM providers including OpenAI, Groq, Gemini, Azure, and local models via Ollama.
Key Features
Use Cases
- 01Extracting company information, founder profiles, and social media links from corporate websites
- 02Scraping product data and pricing from multiple e-commerce pages simultaneously
- 03Converting website content into structured datasets for AI training or analytics pipelines
- 04Automating research by extracting specific information from search engine result pages
- 05Generating Python scraping scripts for recurring data collection tasks
- 06Monitoring website changes by extracting and comparing specific data points over time
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Scrapegraph-ai — FAQ
What is the Scrapegraph-ai MCP server?+
It's an MCP server that brings AI-powered web scraping capabilities to Claude Desktop and other MCP-compatible clients. You describe what data you want to extract in natural language, and the server uses large language models to intelligently scrape websites and return structured JSON results.
How do I install the Scrapegraph-ai MCP server?+
Install the scrapegraphai Python package using pip, then run playwright install to set up browser automation. Configure your MCP client (like Claude Desktop) to connect to the server by adding the appropriate server entry to your configuration file.
Which AI clients work with this MCP server?+
The server works with any MCP-compatible client, including Claude Desktop. It's listed on Smithery and integrates with the Model Context Protocol standard.
Do I need API keys to use Scrapegraph-ai?+
Yes, you need API keys for cloud LLM providers like OpenAI, Groq, Azure, or Gemini. Alternatively, you can use local models through Ollama without API keys, but you must have Ollama installed and models downloaded locally.
Is the Scrapegraph-ai MCP server free?+
The open-source library is free under the MIT License. However, you'll incur costs for LLM API usage with providers like OpenAI or Groq. The managed ScrapeGraphAI cloud API is a separate paid service with per-credit billing.
What's the difference between the open-source library and the managed API?+
The open-source library runs on your own infrastructure and requires you to manage LLM keys, browsers, and proxies. The managed API is a hosted cloud service with built-in anti-bot protection, proxy management, and additional features like crawling and monitoring, billed per credit.
How do I install Scrapegraph-ai?+
Open the source repository on GitHub and follow its README. Scrapegraph-ai is a mcp server — MCP Agents Market links you directly to the official repo.
Is Scrapegraph-ai free?+
Scrapegraph-ai is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.