Company Search
company_searchSearch loaded curated company profiles by name, domain, industry, or ticker. Demo mode allows selected sample queries.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search query, for example technology. |
company_searchSearch loaded curated company profiles by name, domain, industry, or ticker. Demo mode allows selected sample queries.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search query, for example technology. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the 'loaded curated' scope and the demo-mode limitation, which are useful but thin. No contradiction exists between the description and annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the core search behavior and searchable fields are front-loaded, and the demo-mode note adds context without bloating the description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read-only search tool, the description covers the query semantics and the curated nature of the dataset. It lacks any mention of result limits, response shape, or how to use demo mode, but the absence of an output schema and the tool's simplicity keep the gap modest.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only describes q as a generic string with a 'technology' example, giving little semantic guidance. The description compensates by specifying that q may be a name, domain, industry, or ticker, meaningfully enriching the parameter's interpretation beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the operation ('Search') and the resource ('loaded curated company profiles'), and enumerates supported query dimensions: name, domain, industry, or ticker. It is clear on its face but does not differentiate from overlapping siblings like company_lookup_auto or company_ticker, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given on when to choose this tool over the many company_* siblings such as company_lookup_auto, company_domain, or company_ticker. The demo-mode remark is the only contextual hint, and it does not clarify use cases or exclusions. This leaves tool selection largely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.
All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).
129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.
Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.