Namewhere
Server Details
Company name to domain API + MCP: official website, confidence, evidence. $5 pack; 25 free/day.
- Status
- Healthy
- Uptime
- 98.2% over 26 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of confusion or misselection between tools. Its purpose (company name to official domain) is stated clearly and unambiguously.
The single tool uses a clear snake_case noun_to_noun pattern ('company_to_domain') that describes the transformation precisely. With one tool there is no convention to violate.
The server has an extremely narrow, single-purpose surface, and one tool technically covers it, but a one-tool server feels thin and offers no room for adjacent operations. It sits at the borderline of the 1-2 tool guidance.
For the stated narrow purpose of resolving a company name to a domain, the tool is fairly complete, returning confidence, evidence, alternatives, and rejections. Minor gaps remain, such as batch resolution or the reverse lookup (domain to company), but these are outside the core stated scope.
Available Tools
1 toolcompany_to_domainCompany name to official domainARead-onlyIdempotentInspect
Find the official website domain of one company from its name, with confidence 0-1, evidence (Wikidata, homepage brand match), alternatives, rejected look-alikes and social links.
| Name | Required | Description | Default |
|---|---|---|---|
| company | Yes | Company name (or a domain/URL/email to verify) | |
| country | No | Optional ISO-2 country code | |
| minConfidence | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive and open-world, so safety is covered. The description adds genuine behavioral context beyond that: the tool returns a 0-1 confidence score, cites evidence sources (Wikidata, homepage brand match), and surfaces alternatives, rejected look-alikes and social links. It does not say how minConfidence affects the response or what happens on no match, keeping it short of a 5.
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?
A single sentence with the core purpose front-loaded and zero filler. The trailing list of outputs is dense but earns its place since there is no output schema; the one sprawling sentence is the only structural weakness.
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?
With no output schema, the description carries the return-value burden and does it well, naming confidence, evidence, alternatives, rejected look-alikes and social links. Missing details are around the minConfidence threshold's effect on results and failure/ambiguity behavior, which are secondary for a read-only lookup.
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?
Schema coverage is 67%, with the company parameter well documented in the schema. The description adds the meaning of the confidence output (0-1) and implies the verification use of the input, but never explains the country code or the minConfidence default of 0.6 and its filtering behavior. Marginal value over 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?
States a specific verb and resource ('Find the official website domain of one company from its name') and scopes it to a single company, so the agent knows exactly what it resolves. It also enumerates the shape of the answer, which reinforces the purpose. No siblings exist, so differentiation is moot.
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?
Usage is implied by the lookup framing, but there is no explicit statement of when to reach for this tool, what prerequisites exist (e.g. ambiguity handling, rate limits), or when the result should not be trusted. With no siblings the alternative-routing burden is low, but the guidance remains implicit rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- Changed
company_to_domain1 field changed- added
Input schema / properties / company / examplesAdded value: +[ + "Cloudflare" +]
1 tool update
- First observed
company_to_domain
Related MCP Connectors
Namewhere: company name to official website domain, confidence, evidence, socials.
Namewhere: company name to official website domain, confidence, evidence, socials.
GDPR-clean company enrichment: domain, logo, socials, EU VAT and email-security from a name.
Free — no API key required. Enrich by domain or name. Country, contacts, social profiles.
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