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Get contact and business details from a website (paid)

get_business_details
Read-onlyIdempotent

Extract contact and business details from a company website: name, phone numbers (normalised), emails, WhatsApp, postal address, opening hours, social profiles, review platforms, booking and chat tools, UK company and VAT numbers, and page headings. Reads the homepage plus its contact page when the homepage lacks a phone or email. Every value comes from the site itself. Costs 0.02 USDC per completed call, paid automatically via x402 if your client supports it. Never charged if the call fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) URL of the page or website

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations cover safety (readOnly, idempotent, openWorld), and the description adds substantial non-obvious behavior: an explicit price of 0.02 USDC per completed call, automatic x402 payment, a guarantee of no charge on failure, and the two-page crawl strategy. These cost/billing and crawl-scope details are exactly the kind of context an agent cannot get from structured fields.

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

Conciseness5/5

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

Front-loaded with the extraction purpose and field list, then crawl behavior, provenance, and pricing in tight successive sentences. Every sentence carries distinct information with no padding.

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?

With no output schema, the description compensates by enumerating the returned fields and disclosing the billing model and failure behavior. An agent has everything needed to decide to call it and understand the cost implications.

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 one parameter with 100% schema description coverage ('Public http(s) URL of the page or website'), so the schema already fully documents it. The description adds no format or constraint detail about the URL beyond what the schema states, so the baseline of 3 applies.

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?

States a specific verb (Extract) and resource (contact and business details from a company website) and enumerates the exact fields returned. This clearly distinguishes it from siblings like audit_landing_page, check_tracking, and preview_landing_page, which are analysis/preview tools rather than data extraction.

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?

The description explains internal scope (reads homepage plus contact page when the homepage lacks a phone or email), which implies when it is appropriate, but it never states when to prefer this over the sibling audit/preview tools or any exclusions. Usage is implied rather than explicitly routed.

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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