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Crawlora MCP

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web_techstack

Detect the web technologies powering any public URL. Analyze JavaScript frameworks, CMS, e-commerce, analytics, CDNs, and server-side languages with confidence levels.

Instructions

Tech stack — detect what a website is built with. Fetches a public URL and fingerprints the web technologies it is built with — a BuiltWith / Wappalyzer-style detector. Returns a list of detected technologies, each with its categories, a confidence (high, medium, low), an optional version, and the evidence that matched. Covers JavaScript frameworks and libraries (React, Vue.js, Angular, Svelte, jQuery), web frameworks / static site generators (Next.js, Nuxt.js, Gatsby, Remix, SvelteKit, Astro, Hugo), CMS and website builders (WordPress, Drupal, Joomla, Ghost, Wix, Squarespace, Webflow), e-commerce (Shopify, WooCommerce, Magento, BigCommerce), analytics, ad pixels, and tag managers (Google Analytics, Google Tag Manager, Meta Pixel, LinkedIn, Bing, TikTok/Pinterest/Reddit pixels, Segment, Hotjar, Microsoft Clarity), CDNs, UI frameworks and fonts, payments (Stripe, PayPal, Klarna), live chat, marketing automation, A/B testing, consent management, CAPTCHAs (reCAPTCHA, hCaptcha, Turnstile), video, and search. It also inspects response headers (from a plain HTTP fetch) to identify the web server (nginx, Apache, IIS), the CDN / hosting provider (Cloudflare, CloudFront, Fastly, Vercel, Netlify), and the server-side language / framework (PHP, ASP.NET, Ruby on Rails, Django, Laravel, Express). Results are directional, not exhaustive. The render fetch strategy is one of browser (headless browser that executes JavaScript — the default, so client-injected scripts like analytics, tag managers and pixels are detected), auto (Chrome-impersonated HTTP, escalating to a real browser only when blocked or JS-rendered), or http (HTTP only, no JavaScript — fastest, but sees only the server HTML); defaults to browser. Only public pages are supported; respect each site's terms of use and robots directives.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYesTarget URL (and optional render strategy)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden. It discloses that results are directional and not exhaustive, explains the render strategies and their implications, and describes the output fields. It lacks mention of potential errors or rate limits, but covers key behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and then provides extensive lists of covered technologies. While verbose, every sentence adds value and it is well-structured. A slight trim could improve conciseness, but it remains clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (no output schema, nested objects), the description comprehensively covers inputs, outputs, and behavior. It describes the output structure (technologies with categories, confidence, version, evidence) and explains the fetch strategies. No critical gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% but the description adds substantial meaning beyond the schema. It explains the `render` field's three options (browser, auto, http) with details on when each is appropriate, and clarifies the default. The description transforms a simple parameter into a well-understood choice.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: detect what a website is built with, like BuiltWith/Wappalyzer. It specifies the verb 'detect' and resource 'website tech stack', and distinguishes from any sibling tools (none are similar). The long list of covered technologies reinforces its scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says only public pages are supported and to respect terms and robots directives. It explains the render strategy options and defaults, but doesn't contrast with alternatives (no direct sibling). The guidance is clear for correct use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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