KYB due diligence

Company Financials API: UK, Denmark (CVR), Norway accounts

company_accounts

Read-onlyIdempotent

Get normalized financials of UK, Danish and Norwegian companies, including private ones, straight from the official accounts they file with Companies House (UK), Erhvervsstyrelsen (Denmark) and the Brønnøysund Register of Company Accounts (Norway): revenue, gross profit, operating profit, net income, equity, net assets, current assets, cash, creditors and employees. Every number comes with the exact fact or field it was taken from, so you can audit any value. Each row also gets the company's LEI from GLEIF when it has one. Look up companies by company number, CVR or organisation number, or get the newest filings. For credit checks, KYB, M&A and lead research, and for AI agents.

Price: $0.04 per company-year.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "company_accounts"
  }
}

Input Schema

Name	Required	Description
`countries`	No	Registers to read, as codes: GB (Companies House), DK (Erhvervsstyrelsen), NO (Brønnøysund Regnskapsregisteret), BE
`enrichLei`	No	true (default) = look up each company's Legal Entity Identifier at GLEIF by its registration number and add `lei` and `lei_status` (null when the company has no LEI)
`cvrNumbers`	No	Danish CVR numbers, 8 digits, e.g. ["24256790"]
`maxResults`	No	Maximum company-years per country, newest filings first, e.g. 1 for a company's latest accounts
`orgNumbers`	No	Norwegian organisation numbers, 9 digits, e.g. ["923609016"]
`companyNumbers`	No	UK Companies House numbers, e.g. ["03117531", "SC123456"] (shorter numbers are zero-padded to 8)
`enterpriseNumbers`	No	Belgian KBO/BCE enterprise numbers, 10 digits with or without dots, e.g. ["0403.170.701"]

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 8, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Beyond the annotations, the description discloses official data sources, includes an audit trail for every number, explains GLEIF LEI enrichment, and states pricing at $0.04 per company-year. This adds meaningful behavioral context, though it does not cover pagination, error behavior, or full return structure.

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 purpose and data sources are front-loaded, and most sentences earn their place by describing provenance, fields, lookup modes and pricing. There is some mild promotional padding such as 'and for AI agents', but the description remains compact for the amount of useful context it supplies.

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?

For a seven-parameter, read-only financial data tool with no output schema, the description is largely complete: it identifies sources, fields, lookup modes, auditability and pricing. The main gap is that it describes only UK, Danish and Norwegian coverage while the schema also supports Belgium, which could cause an agent to overlook that supported lookup path.

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 the schemas already document identifiers, defaults, limits and LEI enrichment. The description mentions lookup identifiers and newest filings but adds little parameter-specific meaning beyond what the schema provides, and it omits the Belgian enterprise number parameter that is present in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb-resource pair: 'Get normalized financials' for UK, Danish and Norwegian companies, including private ones, with named official registers. It is clear what the tool returns, but it does not explicitly distinguish itself from siblings such as company_check or counterparty_check.

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?

It gives clear usage context: look up companies by company number, CVR or organisation number, or retrieve newest filings, and it lists use cases such as credit checks, KYB, M&A and lead research. It does not name alternative sibling tools or state when not to use this tool, so it falls short of explicit when/when-not guidance.

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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