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registry-mcp — national company registries

by io.github.foretak

Fetch one company record (ChatGPT connector alias for lookup_company)

fetch
Read-onlyIdempotent

ChatGPT connector alias; other clients should prefer lookup_company plus company_deadlines, which return the CompanyReport and DeadlineReport shapes directly. Takes one id from search — "{COUNTRY}:{identifier}", e.g. "NO:923609016" — and returns that company's register record and statutory filing deadlines as readable text, with both full JSON documents in metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesAn `id` from a `search` result: '{COUNTRY}:{identifier}', e.g. 'NO:923609016' or 'GB:00445790'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
urlYes
textYes
titleYes
metadataNo

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds substantial behavioral detail: the output is readable text for the register record and deadlines, and both full JSON documents are included in `metadata`. This goes beyond annotations and helps the agent understand the response shape.

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?

The description is three sentences with no wasted words. It front-loads the alias clarification, then gives the parameter constraint and return behavior. Every sentence contributes essential guidance.

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 single-parameter read-only tool with a rich output schema and detailed annotations, this description is complete. It tells the agent when to use it, what input to provide, and what output to expect, leaving no critical gap.

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?

The schema already documents the `id` format with examples, so the baseline is 3. The description adds value by explicitly stating that the `id` comes from a `search` result and showing the exact `{COUNTRY}:{identifier}` pattern, reinforcing parameter provenance.

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 that `fetch` is a ChatGPT connector alias for `lookup_company` and specifies what it returns: a company's register record and statutory filing deadlines. It distinguishes itself from the sibling tools by noting that other clients should prefer `lookup_company` plus `company_deadlines`.

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?

The description explicitly says when to use this tool (ChatGPT connector) and when not to (other clients should use `lookup_company` plus `company_deadlines`). It also explains that the `id` comes from a `search` result, giving clear invocation context.

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.

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