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Agent Data Broker

Search companies

search_companies
Read-onlyIdempotent

Free preview. Find companies whose name, domain, industry or description contains the query (case-insensitive substring, not semantic). Use this to discover companies or resolve a partial name to a domain, then call get_company_enrichment (paid) for the full record. Returns { count, companies: [{ name, domain, industry }] }, best name matches first; an empty list means no matches. Default 10 results, max 25. Free.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum results (default 10)
queryYesText to look for, e.g. "robotics" or "fintech"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations: matching semantics (not semantic search), result ordering ('best name matches first'), empty-list meaning, result cap of 25, and cost signalling. These are the traits an agent cannot infer from structured fields and would otherwise guess wrong about.

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?

Front-loads the preview framing and packs semantics, sibling routing, return shape and limits into a tight block with no filler. 'Free preview' at the start and 'Free.' at the end are mildly redundant, costing it a perfect score.

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?

No output schema exists, and the description compensates by describing the return shape { count, companies: [{ name, domain, industry }] } along with ordering and empty-result semantics. Combined with match semantics and limits, nothing needed to call it correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description still adds real meaning by clarifying that the query is a substring match rather than semantic and by restating the 10/25 limit behavior in context, though it doesn't add format guidance beyond the schema's own example.

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 and resource ('Find companies') and immediately narrows the matching model to case-insensitive substring across name, domain, industry and description. It explicitly separates itself from the enrichment sibling, so an agent can choose without opening either schema.

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

Usage Guidelines5/5

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

Gives both the discovery use case ('discover companies or resolve a partial name to a domain') and the follow-up path ('then call get_company_enrichment (paid) for the full record'). The free-vs-paid boundary is stated, which is exactly the decision point an agent needs.

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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