Integrate with Scraper.is API for efficient web scraping, data extraction, and web page scraping from any website, perfe
by ai-quill·Updated Apr 13, 2026Fetch 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
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Scraper.is is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Scraper.is reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Scraper.is has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Scraper.is has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Scraper.is benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Useful MCP listing: Scraper.is is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated Scraper.is against two servers with overlapping tools; this profile had the clearer scope statement.
Strong directory entry: Scraper.is surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We wired Scraper.is into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated Scraper.is against two servers with overlapping tools; this profile had the clearer scope statement.
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Claude Desktop configuration
{
"mcpServers": {
"scraperis_scraper": {
"command": "npx",
"args": [
"scraperis-mcp"
],
"env": {
"SCRAPERIS_API_KEY": "your-api-key-here",
"DEBUG": "*"
}
}
}
}Connects to the Scraper.is API to extract web content and convert it to structured formats like Markdown or JSON. Takes screenshots of web pages for visual analysis.
Scraper.is is an official MCP server published by ai-quill that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with Scraper.is API for efficient web scraping, data extraction, and web page scraping from any website, perfe It is categorized under search web.
You can install Scraper.is 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.
A Model Context Protocol (MCP) integration for Scraper.is - A powerful web scraping tool for AI assistants.
This package allows AI assistants to scrape web content through the MCP protocol, enabling them to access up-to-date information from the web.
To install scaperis-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @Ai-Quill/scaperis-mcp --client claude
npm install -g scraperis-mcp
Or with yarn:
yarn global add scraperis-mcp
You need a Scraper.is API key to use this package.
Create a .env file with your Scraper.is API key:
SCRAPERIS_API_KEY=your_api_key_here
To use this package with Claude Desktop:
Install the package globally:
npm install -g scraperis-mcp
Add the following configuration to your claude_desktop_config.json file:
{
"mcpServers": {
"scraperis_scraper": {
"command": "scraperis-mcp",
"args": [],
"env": {
"SCRAPERIS_API_KEY": "your-api-key-here",
"DEBUG": "*"
}
}
}
}
Replace your-api-key-here with your actual Scraper.is API key.
Restart Claude Desktop to apply the changes.
For development and testing, you can use the MCP Inspector:
npx @modelcontextprotocol/inspector scraperis-mcp
This package is designed to be used with AI assistants that support the Model Context Protocol (MCP). When properly configured, the AI assistant can use the following tools:
The scrape tool allows the AI to extract content from websites. It supports various formats:
markdown: Returns the content in markdown formathtml: Returns the content in HTML formatscreenshot: Returns a screenshot of the webpagejson: Returns structured data in JSON formatExample prompt for the AI:
Can you scrape the latest news from techcrunch.com and summarize it for me?
Scrapes content from a webpage based on a prompt.
Parameters:
prompt (string): The prompt describing what to scrape, including the URLformat (string): The format to return the content in (markdown, html, screenshot, json, quick)Example:
{
"prompt": "Get me the top 10 products from producthunt.com",
"format": "markdown"
}
Clone the repository:
git clone https://github.com/Ai-Quill/scraperis-mcp.git
cd scraperis-mcp
Install dependencies:
npm install
Build the project:
npm run build
npm run build: Build the projectnpm run watch: Watch for changes and rebuildnpm run dev: Run with MCP Inspector for developmentnpm run test: Run testsnpm run lint: Run ESLintContributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file 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.