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Company Identity Resolver MCP Server

Resolve Company Identity

resolve_company_identity
Read-onlyIdempotent

Resolves any combination of company name, domain, or LinkedIn URL into the canonical identity with confidence scores and match method, cross-checking inputs and flagging conflicts.

Instructions

Resolve any combination of company name, domain, or LinkedIn URL into one canonical company identity: the name, primary domain, and LinkedIn company URL, each with a 0-100 confidence score plus an overall score and a match method. Cross-checks the inputs you give it, resolves the ones you do not, and flags conflicts (a domain and a LinkedIn slug that disagree) instead of merging them. Login-free and public-data only. Returns flat Clay-ready JSON. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameNoCompany name, e.g. Stripe. Provide at least one of company_name, domain, or linkedin_url.
domainNoBare company domain, e.g. stripe.com. The strongest canonical key when provided.
linkedin_urlNoLinkedIn company URL (https://www.linkedin.com/company/stripe) or bare slug (stripe).
skipCacheNoForce a fresh resolution and ignore the 7 day result cache.
Behavior5/5

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

Annotations already provide readOnlyHint, idempotentHint, etc. The description adds important behavioral details: login-free, public-data only, cross-checks inputs, flags conflicts, requires APIFY_TOKEN, and consumes credits. No contradictions with annotations.

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?

The description is two sentences but packs significant information. While the second sentence is long, it efficiently conveys critical behavioral details without being verbose.

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?

No output schema, so the description must explain return values, which it does: name, domain, LinkedIn URL with confidence scores, overall score, match method. It also mentions JSON format and cost. Some minor gaps (e.g., no mention of error handling) but adequate given other richness.

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 baseline is 3. The description adds value by clarifying domain is the strongest canonical key, explaining linkedin_url accepts URL or bare slug, and describing skipCache behavior. This justifies a score above baseline.

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?

The description clearly states the tool resolves any combination of company name, domain, or LinkedIn URL into a canonical identity. It specifies inputs and outputs, leaving no ambiguity about its function.

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

Usage Guidelines4/5

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

The description explains when to use the tool (to resolve company identity from partial info) and mentions cross-checking and conflict detection. However, no explicit when-not-to-use guidance is given, but this is acceptable given no sibling tools exist.

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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