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Technologies used by a website

website_technologies
Read-only

Technologies used by a website. Detect technologies. Detect 130+ technologies a website uses: CMS (WordPress, Shopify, Wix, Webflow), frameworks (React, Next.js, Vue), analytics and pixels, chat, CDN and hosting. Great for lead generation and competitor research.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite URL (e.g. https://wordpress.org)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety basics are covered. The description adds useful scope detail ('130+ technologies', category coverage) that partially substitutes for the absent output schema, though it says nothing about rate limits, auth needs or failure behavior.

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

Conciseness3/5

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

The first and second sentences restate the title ('Technologies used by a website. Detect technologies.'), which is pure redundancy. The category enumeration is front-loaded and informative, but the opening wastes space before delivering the actual value.

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

Completeness4/5

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

For a one-parameter, read-only detection tool, the description is largely complete: it tells the agent what class of technologies is returned, which compensates for the missing output schema. It could still note the return shape (e.g. category-to-technology mapping) more explicitly.

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

Parameters3/5

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

There is a single parameter and schema description coverage is 100%, with the schema itself supplying the URL format example. The description adds no extra semantics about the url argument. Baseline 3 applies when the schema does all the work.

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

Purpose4/5

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

States a specific verb ('Detect') and resource ('technologies a website uses'), then enumerates the covered categories (CMS, frameworks, analytics, chat, CDN/hosting) and scope ('130+ technologies'). This implicitly distinguishes it from near-neighbors like seo_audit, security_headers_check and dns_lookup, though no sibling is named explicitly.

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

Usage Guidelines3/5

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

'Great for lead generation and competitor research' gives intent-level context but never states when to call this versus alternatives such as seo_audit or check_url_status. Usage is implied by the use-case framing rather than spelled out.

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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