Crawlbase MCP. Extract structured data from any website, no coding required.
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Crawlbase connects your AI agent to a full web scraping suite. It lets you extract structured data from Amazon, LinkedIn, Facebook, and Google SERPs.
You can scrape general HTML, handle JavaScript-rendered pages, and even capture screenshots of target sites. It also manages custom proxies and bypasses CAPTCHAs via natural conversation.
What your AI agents can do
Custom scrape
Generates custom proxies with specific headers and crawling logic for high-availability requests.
Get screenshot link
Runs a validation check and returns a temporary URL for a web snapshot.
Scrape amazon
Inspects deep internal arrays to extract data from Amazon e-commerce listings.
The agent forces raw web output into a clean, structured JSON format, isolating and extracting required properties from the page.
The agent uses dedicated tools to pull structured data from platforms like LinkedIn, Facebook, Amazon, and X, bypassing site-specific restrictions.
The agent executes JavaScript rendering logic to pull data from modern web pages where content loads after the initial HTML load.
The agent runs validation checks to generate a screenshot link for any given web endpoint, proving the content was successfully retrieved.
The agent generates custom proxies with defined headers and specific crawling logic, allowing you to control the source of the request.
The agent targets Google domains with mapped proxy lists to parse Search Engine Results Pages (SERPs) and manage CAPTCHA challenges.
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Crawlbase MCP Server: 10 Web Scraping Utilities
These tools let you scrape data from specific sites, handle dynamic JavaScript, manage proxies, and structure raw web content using natural language prompts.
019d757ecustom scrape
Generates custom proxies with specific headers and crawling logic for high-availability requests.
019d757eget screenshot link
Runs a validation check and returns a temporary URL for a web snapshot.
019d757escrape amazon
Inspects deep internal arrays to extract data from Amazon e-commerce listings.
019d757escrape facebook
Exports structured data from active Facebook social pages.
019d757escrape google serp
Parses Google search results by identifying active arrays within rented Context domains.
019d757escrape html
Extracts explicitly attached HTML content using datacenter proxies inside the headless engine.
019d757escrape js rendered
Retrieves data from dynamically loaded web pages by tracing explicit Cloud logging payloads.
019d757escrape json format
Performs structural extraction, turning raw page properties into usable JSON fields.
019d757escrape linkedin
Pulls structured data from LinkedIn profiles while verifying Blueprint constraints.
019d757escrape twitter
Fetches structured data from X/Twitter graphs using dedicated Crawlbase extraction.
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
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- 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 Crawlbase, 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
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Crawlbase connects your AI agent to a full web scraping suite. You'll use it to pull structured data from Amazon, LinkedIn, Facebook, and Google SERPs. You can scrape general HTML, handle JavaScript-rendered pages, and even grab screenshots of any site. You also manage custom proxies and bypass CAPTCHAs with just talking to your agent.
When you need to pull structured data, your agent forces raw web output into a clean JSON format, isolating and grabbing the specific properties you need from any page. For social media, it uses dedicated tools to pull structured data from LinkedIn, Facebook, Amazon, and X, getting around site-specific restrictions.
If the content loads with JavaScript, the agent runs rendering logic to pull data from modern web pages. You can prove the content was retrieved by running validation checks that generate a temporary URL for any site snapshot. You control the source of the request by having the agent generate custom proxies with defined headers and specific crawling logic.
You can target Google domains with mapped proxy lists to parse Search Engine Results Pages (SERPs) and handle CAPTCHA challenges. To extract general content, your agent uses scrape_html to grab explicitly attached HTML content using datacenter proxies inside a headless engine. When you need to get data from Amazon, the agent uses scrape_amazon to inspect deep internal arrays and extract listings.
For Facebook pages, it uses scrape_facebook to export structured data from active pages. For Google searches, it uses scrape_google_serp to parse results by identifying active arrays within rented Context domains. When you're on LinkedIn, the agent uses scrape_linkedin to pull structured data from profiles while verifying Blueprint constraints. For X/Twitter, you use scrape_twitter to fetch structured data from graphs using dedicated Crawlbase extraction.
If the page content loads dynamically, you use scrape_js_rendered to retrieve data by tracing explicit Cloud logging payloads. For structural extraction, you use scrape_json_format to perform structural extraction, turning raw page properties into usable JSON fields. Finally, you can get a snapshot of a site using get_screenshot_link which runs a validation check and returns a temporary URL for a web snapshot.
How Crawlbase MCP Works
- 1 Subscribe to the Crawlbase server and provide your Normal Token and optional JavaScript Token to your AI client.
- 2 Instruct your agent to perform a task, such as 'Scrape the price from this Amazon listing' or 'Get a screenshot of X URL'.
- 3 The agent executes the specific tool (e.g.,
scrape_amazon), and you receive the structured data, JSON output, or screenshot URL.
The bottom line is you get to treat web scraping like calling a function in code, using natural language instead.
Who Is Crawlbase MCP For?
Data Analysts who need structured web data without writing code. Market Researchers needing deep web crawls and site snapshots. Growth Hackers monitoring competitors across Amazon and social platforms. Developers testing complex extraction pipelines.
Extract structured data and search results from web pages without writing complex scraping scripts.
Perform deep web crawls and capture snapshots of target sites for offline analysis of market trends.
Monitor competitor products on Amazon or track social profiles on LinkedIn and Twitter in real-time for competitive intelligence.
Test and debug complex web extraction pipelines and JavaScript-rendering logic through natural conversation.
What Changes When You Connect
- Need to scrape a competitor's product page? Use
scrape_amazonto inspect deep internal arrays and pull structured data from Amazon listings. - Can't get the data because it loads with JavaScript? Run
scrape_js_renderedto track explicit Cloud logging, ensuring you capture content loaded dynamically. - Working with social media? Use
scrape_linkedinorscrape_facebookto get structured data from profiles and pages, bypassing site restrictions. - Need to analyze search results?
scrape_google_serptargets Google domains directly, letting you parse SERPs and manage CAPTCHA challenges. - Want clean, usable data? Use
scrape_json_formatto force raw HTTP output into a strict, structured JSON format. - Need to prove the page content? Run
get_screenshot_linkto dispatch a validation check and get a valid screenshot URL.
Real-World Use Cases
Tracking competitor product changes
A growth hacker needs to monitor price changes for a key product on Amazon. They ask their agent to run scrape_amazon repeatedly. The agent extracts the title, price, and rating into a structured JSON output, allowing the hacker to build a change log without manual data entry.
Deep research on industry thought leaders
A market researcher needs to gather data from multiple sources. They run scrape_linkedin to collect profile details, then use scrape_twitter to pull related activity, and finally use scrape_google_serp to find articles linking those people. The agent synthesizes all three data streams into a cohesive set of intelligence.
Debugging a complex web pipeline
A developer hits a wall trying to get data from a modern site. They use scrape_js_rendered to capture the dynamic content, then pass it to scrape_json_format. The agent successfully extracts the data, proving the content was visible to the headless engine.
Analyzing a large batch of targeted web pages
A team needs to validate 50 target URLs. They use get_screenshot_link to automate validation checks, generating a screenshot for each endpoint. This provides visual proof that the content was successfully rendered before the data extraction begins.
The Tradeoffs
Using general scraping for specific sites
Trying to scrape a LinkedIn profile using only scrape_html because it's the general tool. This fails because LinkedIn uses specific internal structures and requires a specialized method.
→
Always use the targeted tool. For LinkedIn data, use scrape_linkedin. For Amazon, use scrape_amazon. General tools like scrape_html are only for fallback or simple pages.
Ignoring dynamic content
Running a scrape on a modern site and getting incomplete data because the content only loads after a user scrolls or clicks (JS rendering).
→
Use scrape_js_rendered instead of scrape_html. This tool handles the JavaScript execution, making sure the agent sees the full page content before attempting extraction.
Forgetting to structure the output
The agent returns a giant block of raw text from a webpage, making it impossible to use in a database or spreadsheet.
→
Pipe the output through scrape_json_format. This forces the raw data into a predictable, structured JSON format, which is ready for immediate use.
When It Fits, When It Doesn't
Use Crawlbase if your goal is reliable, structured data from diverse, high-security websites. You need it when general web scraping fails due to JavaScript, anti-bot measures, or site-specific complexity. Don't use it if your data sources are simple, static HTML files you can access via a basic HTTP request. If you only need raw text and don't care about structure, you might get away with scrape_html, but you'll miss out on the powerful, reliable data shaping and specialized tools like scrape_amazon and scrape_linkedin that guarantee usable, clean output.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Crawlbase. 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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Managed infra
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Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
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EU data residency
Token Compression
~60% cost reduction
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 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Manually scraping data feels like a full-time job.
Today, getting web data means opening ten tabs: one for Amazon, one for LinkedIn, one for Google, and then figuring out how to scrape the JS-loaded parts. You're copying URLs, running separate scripts, and then manually cleaning up the messy, non-standardized text dumps into a spreadsheet. It's a messy, multi-hour process.
With Crawlbase, you just tell your agent what you need—say, 'Get the price and rating from this Amazon listing.' The agent runs `scrape_amazon`, handles the complexity of the site, and gives you the clean, structured JSON data, period.
Crawlbase MCP Server: Get structured data from any website.
You don't have to write a separate script for every single website. You run the command through the agent, and it chooses the right tool—whether it's `scrape_facebook` for social pages or `scrape_js_rendered` for dynamic content. It handles the plumbing.
What's different now is that the data comes out ready for analysis. No more dirty HTML dumps. Just clean, actionable JSON.
Common Questions About Crawlbase MCP
How do I scrape data from Amazon using Crawlbase MCP Server? +
You use the scrape_amazon tool. This specialized tool inspects deep internal arrays, ensuring you extract the correct title, price, and features from the Amazon listing.
Can I scrape Google search results with the crawlbase MCP Server? +
Yes, use scrape_google_serp. This tool targets Google domains with mapped proxy lists to parse the SERP results and manage CAPTCHA limits.
What if the page has JavaScript, can crawlbase MCP Server handle it? +
Yes, use scrape_js_rendered. This tool executes JavaScript logging to retrieve data from pages where content loads dynamically, giving you the full page content.
How do I make the output data usable in my scripts with Crawlbase MCP Server? +
Run scrape_json_format. This tool takes raw extracted content and forces it into a standardized, structured JSON format that your agent can easily process.
How do I manage proxies when using Crawlbase MCP Server? +
Use custom_scrape to provision custom proxies. This lets you generate request payloads with specific headers and crawling logic, giving you full control over the request source.
How do I use the `scrape_json_format` tool with the Crawlbase MCP Server? +
This tool forces raw HTTP outputs into structured JSON format. You pass it the data you want, and it analyzes the global bounds to guarantee a clean, machine-readable JSON structure.
Can I use the `custom_scrape` tool to set up my proxies with the Crawlbase MCP Server? +
Yes, the custom_scrape tool provisions highly-available request payloads. You can generate custom proxies by defining specific headers and the exact crawling logic you need.
What are the best practices for using the `scrape_google_serp` tool? +
The scrape_google_serp tool targets Google domains, letting you parse SERP limits and bypass CAPTCHAs. It works by identifying precise active arrays spanning those search result pages.
When should I use the JavaScript (JS) Token versus the Normal Token? +
Use the Normal Token for fast, static HTML extraction. Switch to the JavaScript Token when the target site uses frameworks like React or Angular, where content is rendered dynamically in the browser. The 'scrape_js_rendered' tool requires the JS Token to function.
Can my agent bypass CAPTCHAs while scraping Google or LinkedIn? +
Yes. Crawlbase is built to handle CAPTCHAs and blocks natively. When you use specialized tools like 'scrape_google_serp' or 'scrape_linkedin', the agent routes your requests through Crawlbase's advanced proxy infrastructure to ensure successful data extraction.
How do I get a structured JSON response instead of raw HTML? +
Use the 'scrape_json_format' tool or the specialized scraper tools (Amazon, LinkedIn, etc.). These trigger Crawlbase's auto-extraction pipelines, which analyze the page structure and return specific data fields in a clean JSON format.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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