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registry-mcp — national company registries

by io.github.foretak

Validate a company identifier (no network call)

validate_company_id
Read-onlyIdempotent

Check whether a national company identifier is well-formed — no network call.

country="NO" checksum-checks a Norwegian organisasjonsnummer (orgnr, org.nr) for Brønnøysundregistrene / Enhetsregisteret (brreg); this is the cheap norway company lookup pre-check for the norwegian business registry. country="GB" shape-checks and normalises a UK company number (company registration number, CRN) for Companies House: it zero-pads a short number ('445790' → '00445790') and upper-cases a prefix ('oc303675' → 'OC303675'). A CRN has no check digit, so a GB valid: true means the shape is right and nothing more.

Use it on user input or a spreadsheet column before spending a real lookup_company call, since it is instant and free.

Returns a ValidationResult and never raises for a malformed identifier: valid: false comes with reason (what failed) and hint (what to do next) rather than a tool error — this tool answers a question, it does not fail on bad input (DECISIONS.md D-010). A valid identifier does not mean the entity exists; follow it with lookup_company if you need facts.

The only real error here is unsupported_country (no module for that country yet — call list_countries), raised with the error text {"error": {"code", "message", "hint"}}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe company's national identifier. Norway (country='NO'): a nine-digit organisasjonsnummer (orgnr), e.g. '923609016'; spaces, dots and a 'NO...MVA' VAT suffix are accepted and normalised. United Kingdom (country='GB'): a Companies House company number (CRN), eight characters, e.g. '00445790' or 'OC303675'; a short number is zero-padded for you.
countryNoISO-3166-1 alpha-2 country code. 'NO' = Norway (Brønnøysundregistrene / Enhetsregisteret), 'GB' = United Kingdom (Companies House). 'UK' is not a country code here and is rejected. Call list_countries for the current set rather than hard-coding one.NO

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNoWhat to do next when `valid` is false — the same hint the invalid_id error carries. None when valid: the next call is simply lookup.
inputYesThe identifier exactly as the caller supplied it.
validYesTrue when the identifier passes this country's format and checksum.
reasonNoOne English sentence saying why it is valid, or what failed.
countryYesISO-3166-1 alpha-2, upper-case.
registryYesRegistry slug, e.g. 'brreg'.
formattedNoThe identifier as a local would write it, e.g. '923 609 016'. None when invalid.
id_schemeNoName of the identifier scheme, e.g. 'organisasjonsnummer'.
normalizedNoCanonical form to pass to lookup, e.g. '923609016'. None when invalid.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and the description is fully consistent with them. Beyond that, it discloses meaningful behavioral traits: it never raises for malformed identifiers and returns reason/hint instead of a tool error, it performs no network call, country-specific semantics (checksum vs. shape-check, zero-padding, upper-casing), and the exact error shape for unsupported_country. This far exceeds what annotations provide.

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 long (five paragraphs) but every paragraph carries distinct non-redundant information: core purpose, country behavior, usage guidance, return/error behavior, and the sole error case. It is front-loaded with the most important fact ('Check whether... no network call') and uses paragraphs as structural separators. Slight redundancy exists between title and first sentence ('no network call'), but no sentence is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter validation tool with an output schema and full annotations, nothing essential is missing. It covers per-country validation rules, the false-positive caveat (valid ≠ exists), the correct follow-up tool, normalization details for the id parameter, and the only error condition with its payload shape. The DECISIONS.md reference adds traceability for the no-failure contract.

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 description coverage is 100% so the baseline is 3, but the description adds substantive meaning: it explains WHY country values behave differently (NO checksums against brreg; GB shape-only with no check digit), the normalization consequences for id ('445790' → '00445790'), and rejects 'UK'. The schema documents formats, but the description explains the validation semantics and practical implications.

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 opening sentence states a specific verb and resource: 'Check whether a national company identifier is well-formed — no network call.' It clearly differentiates from siblings by positioning itself as the cheap pre-check before lookup_company, and more granularly separates NO checksum validation from GB shape-checking. An agent can distinguish this from the six sibling tools without opening their schemas.

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

Usage Guidelines5/5

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

Explicit when-to-use guidance is present: 'Use it on user input or a spreadsheet column before spending a real lookup_company call, since it is instant and free.' It also names the follow-up alternative ('follow it with lookup_company if you need facts'), the exclusion condition for GB ('A CRN has no check digit, so a GB valid:true means the shape is right and nothing more'), and routes unsupported countries to list_countries.

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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TDQS

A4.4/5.0
Disambiguation3/5

There are two pairs of conceptually overlapping tools: lookup_company vs validate_company_id (both take a country code and identifier, and validate_company_id explicitly positions itself as a 'pre-check' or 'cheap' version of lookup_company), and search vs search_company vs fetch vs company_deadlines (the connector aliases duplicate the canonical tools). The descriptions do disambiguate them, but an agent could reasonably confuse validate_company_id with a lightweight lookup rather than a pure format check, and the alias pair search/fetch adds unnecessary ambiguity.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern: list_countries, lookup_company, search_company, validate_company_id, company_deadlines. However, company_deadlines breaks the pattern by putting the noun first without a verb, and fetch/search are generic aliases that do not match the family's naming convention. The core set is consistent, but the deviations are noticeable.

Tool Count4/5

Seven tools is within the ideal range for a domain-specific registry server. The main tools (list_countries, search_company, lookup_company, company_deadlines, validate_company_id) each earn their place. The two connector aliases (search, fetch) are somewhat redundant for non-ChatGPT clients, which slightly pads the count without adding real functionality, but the scope is still reasonable.

Completeness5/5

The tool surface covers the full lifecycle of a company-registry interaction: discover supported countries (list_countries), validate an identifier offline (validate_company_id), search by name (search_company), fetch full company data (lookup_company), and retrieve statutory deadlines (company_deadlines). There are no obvious dead ends: search returns ids that feed lookup_company, and lookup_company complements deadlines. For the stated purpose—answering company identity and filing-deadline questions from national registries—the coverage is complete.

Resources