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ScrapeGraphAI/Scrapegraph-ai

ScrapeGraphAI/Scrapegraph-ai

Python scraper based on AI
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Source
collected from the abordage/awesome-mcp list · type: MCP server
Harvest history
first seen 2026-10-14 · last seen 2026-10-16 · seen 4× · listed by 3 sources
Score
score 303 · 3 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-10-14;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals

🚀 **Looking for an even faster and simpler way to scrape at scale (only 5 lines

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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🕷️ ScrapeGraphAI: You Only Scrape Once
English | 中文 | 日本語
| 한국어
| Русский | Türkçe
| Deutsch
| Español
| français
| Português
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ScrapeGraphAI is a *web scraping* python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.).
Just say which information you want to extract and the library will do it for you!
🚀 Integrations
ScrapeGraphAI offers seamless integration with popular frameworks and tools to enhance your scraping capabilities. Whether you're building with Python or Node.js, using LLM frameworks, or working with no-code platforms, we've got you covered with our comprehensive integration options..
You can find more informations at the following link
**Integrations**:
- **API**: Documentation
- **SDKs**: Python, Node
- **LLM Frameworks**: Langchain, Llama Index, Crew.ai, Agno, CamelAI
- **Low-code Frameworks**: Pipedream, Bubble, Zapier, n8n, Dify, Toolhouse
- **MCP server**: Link
🚀 Quick install
The reference page for Scrapegraph-ai is available on the official page of PyPI: pypi.
**Note**: it is recommended to install the library in a virtual environment to avoid conflicts with other libraries 🐱
💻 Usage
There are multiple standard scraping pipelines that can be used to extract information from a website (or local file).
The most common one is the SmartScraperGraph, which extracts information from a single page given a user prompt and a source URL.
> [!NOTE]
> For OpenAI and other models you just need to change the llm config!
>
The output will be a dictionary like the following:
There are other pipelines that can be used to extract information from multiple pages, generate Python scripts, or even generate audio files.
| Pipeline Name | Description |
|-------------------------|------------------------------------------------------------------------------------------------------------------|
| SmartScraperGraph | Single-page scraper that only needs a user prompt and an input source. |
| SearchGraph | Multi-page scraper that extracts information from the top n search results of a search engine. |
| SpeechGraph | Single-page scraper that extracts information from a website and generates an audio file. |
| ScriptCreatorGraph | Single-page scraper that extracts information from a website and generates a Python script. |
| SmartScraperMultiGraph | Multi-page scraper that extracts information from multiple pages given a single prompt and a list of sources. |
| ScriptCreatorMultiGraph | Multi-page scraper that generates a Python script for extracting information from multiple pages and sources. |
For each of these graphs there is the multi version. It allows to make calls of the LLM in parallel.
It is possible to use different LLM through APIs, such as **OpenAI**, **Groq**, **Azure**, **Gemini**, **MiniMax** and more, or local models using **Ollama**.
Remember to have Ollama installed and download the models using the **ollama pull** command, if you want to use local models.
📖 Documentation
The documentation for ScrapeGraphAI can be found here.
🆚 Open Source vs Managed API
ScrapeGraphAI comes in two flavours: **this open-source library**, which you run yourself, and the **managed cloud API** (used via the Python and JS/TS SDKs). This table explains the difference so you can pick the right one.
Source
awesome · https://github.com/ScrapeGraphAI/Scrapegraph-ai
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