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Company Search

company_search
Read-only

Find companies worldwide by name in the official GLEIF register of legal entities: legal name, LEI, country, registered address, company-register number, legal form and status, best match first, plus matching US-listed companies with ticker and SEC CIK. Costs USD 0.005 per call, paid with x402 (USDC on Base); calls that fail are not charged.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "company_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many matches (default 5)
queryYesCompany name, e.g. Reliance Industries
countryNoOptional two-letter country code to narrow the search, e.g. IN

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, non-destructive and non-idempotent. The description adds genuinely non-derivable behavior: USD 0.005 per call, paid via x402 (USDC on Base), failing calls are not charged, and results are ordered best match first. It does not discuss rate limits or result stability across calls.

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?

Two sentences, zero filler: the first front-loads what is searched and what comes back, the second covers cost and payment. Every clause carries information an agent would otherwise lack.

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?

With no output schema, the description usefully enumerates returned fields and cost, and the input schema covers all three parameters. Minor gaps remain around matching behavior (exact vs partial name, transliteration) and result ordering stability, but nothing blocking for correct invocation.

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?

Schema description coverage is 100%, so query, country and limit are already documented with examples and bounds. The description adds no further syntax or matching semantics (fuzzy vs exact, how country filters), so the baseline 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 and resource ('Find companies worldwide by name') plus the authoritative data source (official GLEIF register) and the exact fields returned. The mention of worldwide scope plus US-listed ticker/CIK coverage distinguishes it from the narrower sibling lookups company_lei and company_us.

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 verb 'find by name' implies the use case (name-based discovery), but the description never names company_lei or company_us or states when to prefer them. An agent must infer the boundary from the sibling names alone.

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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