Spider MCP. Scrape, Crawl, Search. Web data extraction at scale.
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…and any MCP-compatible client
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Spider provides high-performance web scraping and crawling via an open MCP Server connection. It lets your AI agent search, scrape single pages, or map entire websites using a Rust engine that runs at extreme speeds (>100K pages/second).
Built-in anti-bot protection and proxy rotation handle the hard stuff, giving you clean data in Markdown, HTML, or plain text format.
What your AI agents can do
Spider crawl
Maps a website by following internal links and scraping content across multiple pages at high speed.
Spider scrape
Scrapes the clean, full content of one specific URL, handling JS rendering and anti-bot measures automatically.
Spider search
Combines web search query processing with scraping, delivering results and their content in a single call.
The spider_crawl tool follows internal links across a whole site, returning content from multiple pages following the structure.
The spider_scrape tool pulls clean text and markup from one page while automatically managing JavaScript rendering and anti-bot measures.
The spider_search tool searches the web and scrapes the content of the top results in a single request, combining discovery with extraction.
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Spider MCP Server: 3 Tools for Web Data Extraction
Use these three tools—search, scrape, and crawl—to extract structured content from any web source at high volume.
019d760bspider crawl
Maps a website by following internal links and scraping content across multiple pages at high speed.
019d760bspider scrape
Scrapes the clean, full content of one specific URL, handling JS rendering and anti-bot measures automatically.
019d760bspider search
Combines web search query processing with scraping, delivering results and their content in a single call.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Spider, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Spider hooks your AI agent into some of the fastest web scraping engine out there. It’s built on a Rust core, meaning it runs at crazy speeds—we're talking over 100K pages per second when you need it. Your agent uses this server to search, scrape individual pages, or even map whole websites.
The system handles all the tough stuff itself: proxy rotation and anti-bot protection are built in so you just get clean data.
Scraping Specific Content with spider_scrape
If you need the full text from one single URL, use spider_scrape. This tool pulls clean content and markup from that page. It automatically deals with JavaScript rendering, which means if a site loads its actual text using JS, your agent still gets it. The system manages anti-bot measures and rotates proxies so nothing breaks in the middle of the scrape.
You'll get the data you need—in Markdown (which is the default), HTML, or plain text format.
Mapping Entire Websites with spider_crawl
When you need more than just one page, run spider_crawl. This tool maps a whole website by following all its internal links. Your agent can recursively follow those connections to extract structured data across dozens of pages without missing a beat or hitting a wall. It essentially builds a map of the site's content structure for you.
Combining Search and Extraction with spider_search
Need both discovery and actual content? Use spider_search. This tool combines web search query processing directly with scraping capabilities in one single request. Your agent gets results from the top sources and the actual text content from those sources instantly, keeping your workflow fast.
How It Works Under the Hood
When you connect your AI client to the MCP Server endpoint and call a tool—spider_crawl, spider_scrape, or spider_search—the high-performance Rust engine takes over. The server processes requests at extreme speed, returning reliable data formatted for immediate use. You're not dealing with complicated infrastructure; you just tell your agent what you need, and the system delivers clean, structured content.
It provides robust support across multiple output formats, including Markdown, HTML, or simple plain text. This means whether you’re feeding the data into a database, running it through another process, or just reading it, the format is ready to go.
How Spider MCP Works
- 1 Subscribe to the server and enter your Spider API key. Your agent uses this key to authenticate.
- 2 Your AI client invokes one of the three specialized tools:
spider_scrapefor a single page,spider_crawlfor a site map, orspider_searchfor web results. - 3 The tool executes the request using its optimized Rust engine and returns the requested content structure (Markdown, HTML, or text) directly to your agent.
The bottom line is: You pass the target URL or query to the right tool, and Spider handles all the complex fetching, anti-bot detection, and data formatting for you.
Who Is Spider MCP For?
Anyone who needs large volumes of clean, structured text from the web. Think market researchers needing competitor content audits, SEO specialists mapping site structures, or academic developers collecting source material. If your job involves reading data off a website at scale, this is for you.
Needs to run spider_crawl on an entire corpus of research papers' websites to ensure full site mapping before building a knowledge base.
Uses spider_scrape repeatedly on competitor landing pages to pull specific copy blocks and check for JavaScript-rendered content changes.
Runs spider_search with industry keywords to gather immediate, structured comparisons from the top three search results without having to click through manually.
What Changes When You Connect
- Speed and Stealth: The Rust engine provides speeds exceeding 100K pages/second while built-in stealth mode handles fingerprint rotation and residential proxies. You get massive throughput without hitting roadblocks.
- Multi-Format Output: Don't just get text.
spider_scrapelets you choose the output format—Markdown (default), HTML, or plain text—so your data is ready for whatever pipeline you use next. - Full Site Mapping: Use
spider_crawlto recursively map entire domains. This ensures you gather structured content from every internal link, which is critical for complete site audits. - Discovery + Extraction: The
spider_searchtool eliminates friction by combining web searching and scraping into one request. You get the best of both worlds instantly. - JS Rendering Handled: Forget missing content because a page uses JavaScript. Both
spider_scrapeandspider_crawlhandle JS rendering automatically, guaranteeing you pull all visible text.
Real-World Use Cases
Conducting a full competitive audit
A market researcher needs to understand the content depth of three competitors. Instead of manual checks, they use spider_crawl on each site to map all internal pages and extract structured data, giving them a complete picture of the opposition's published material.
Gathering academic source material
A student is writing a literature review. They run spider_search for 'quantum computing breakthroughs 2025.' The agent finds and scrapes the top three articles in one go, saving hours of manual copy-pasting from different sources.
Extracting product data from single pages
An e-commerce scraper only needs the content from a specific URL. They use spider_scrape, specifying Markdown output. This ensures they get clean, formatted text without worrying about messy HTML tags or JavaScript failures.
Building a niche knowledge base
A developer wants to index all documentation from an open-source project. They run spider_crawl on the docs domain first, then feed the resulting pages into their AI client for indexing. This systematic approach guarantees full coverage.
The Tradeoffs
Treating all scraping as single-page pulls
Running spider_scrape on a site's homepage, then running it again on the 'About Us' page, and so on. This is slow, repetitive, and leaves out linked pages.
→
If you need content from multiple related pages, use spider_crawl. It handles the recursive linking and extraction for the whole site in one optimized operation.
Manually searching and then scraping
First using a general search tool to find 10 articles, opening each link, and running an extractor on every single page. This is slow and prone to failure.
→
Use spider_search. It finds the relevant results and scrapes the content of those top results simultaneously in one API call.
Assuming static website data
Writing code that only pulls simple text when a target site loads its main product descriptions using React or Vue.js.
→
Always use spider_scrape. Its built-in JavaScript rendering capability ensures the content you see in your browser is the content you get back.
When It Fits, When It Doesn't
Use this server if your primary bottleneck is sheer web data volume, speed, or anti-bot evasion. You need high throughput and structured output formats (Markdown/HTML).
Do use it if: 1) You must map a whole site (spider_crawl). 2) You need to gather content from search results immediately (spider_search). 3) You are scraping pages that rely on JavaScript rendering (spider_scrape).
Don't use it if: 1) Your data is already in a clean, structured format (e.g., CSV/JSON). Use a simple database connector instead.
2) The content you need requires user interaction beyond basic reading (e.g., clicking a 'Submit' button that triggers an API call). You'll need specialized form submission tools for that.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Spider. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 3 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Getting data from complex websites is usually slow and messy.
Today, gathering content means hitting multiple tabs. You find a list of articles through Google, copy the URLs, paste them into an extractor tool, wait for it to fail because JavaScript rendered some key paragraphs, then you have to repeat the whole process on the next batch. It's manual, slow, and often incomplete.
With Spider, your agent runs `spider_search` or `spider_crawl`. You give it a query or a domain, and the tool handles the heavy lifting—the JavaScript rendering, the proxy rotation, and the anti-bot measures. The result is clean Markdown or HTML, ready for your next step.
Spider MCP Server: Full site mapping with `spider_crawl`
The old way was crawling a site piece by piece—checking the homepage, then manually finding links to the 'Services' page, and then checking sub-pages from there. This guarantees you miss deep content or structure.
Now, running `spider_crawl` gives your agent full access to the entire linked structure at scale. You get a reliable map of every accessible page without ever having to manually click a single link.
Common Questions About Spider MCP
How do I use spider_scrape for a single product page? +
You call spider_scrape and pass the direct URL. This tool handles JavaScript rendering automatically, so you get clean content regardless of how the site loads its text.
Is spider_crawl better than just scraping a list of URLs? +
Yes. spider_crawl is superior because it understands and follows internal links (sitemap logic). It discovers pages you might not even know exist, ensuring your data set is complete.
Can spider_search scrape the content of search results? +
Yes. That's exactly what spider_search does. It combines finding relevant web links with scraping their actual content in one efficient API call, saving you multiple steps.
What is the performance difference between Spider and other scrapers? +
Spider uses a Rust engine for maximum speed. The listing data shows it can crawl at speeds exceeding 100K pages/second, which dramatically outperforms tools built on Node.js.
What content formats can I get when using spider_scrape? +
The tool supports Markdown, HTML, and plain text outputs. You specify your desired format in the request parameters. This lets you choose the best structure for parsing or saving.
How do I limit the scope when using spider_crawl? +
You configure both the maximum depth and the total page count in the API call. This keeps your crawl focused, preventing unnecessary processing of entire websites.
Does spider_scrape handle modern websites that rely on JavaScript? +
Yes, it handles JS rendering automatically. The service includes built-in support for anti-bot measures and proxy rotation so your requests appear legitimate.
What does using spider_search combine into one call? +
It combines web searching with content extraction in a single, high-performance API request. This saves time and improves efficiency by eliminating the need for two separate calls.
How is Spider different from Firecrawl? +
Spider is built in Rust and optimized for raw speed and volume — it can crawl 100K+ pages per second, making it 10-20x faster than Firecrawl for large-scale operations. Spider also offers lower per-page costs at high volume, built-in stealth mode with fingerprint rotation, and multiple request modes (HTTP, Smart, Chrome). Firecrawl excels at simplicity and LLM-specific features like JSON extraction.
What output formats does Spider support? +
Spider supports Markdown, HTML, raw HTML, plain text, JSON (structured extraction), screenshots, and PDF output. You can specify the desired format via the return_format parameter in each request.
How does Spider pricing work? +
Spider offers 500 free credits to get started (no credit card required). Paid plans are usage-based with credits consumed per page scraped. The Starter plan begins at $15/month with 12,000 credits. Enterprise plans offer custom pricing with dedicated infrastructure and unlimited concurrency.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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