companies-house-screening-mcp

Find an officer

find_officer

Read-onlyIdempotent

Search Companies House for a director, secretary, or LLP member by name and receive candidate officer IDs with appointment counts. Use it to identify which officer matches before retrieving their appointments.

Instructions

Search Companies House for a company officer — a director, secretary or LLP member — by name. Returns candidate officer IDs with how many appointments each holds. Use it when you have a person and want the companies they are involved in; feed the officer_id to get_officer_appointments. Officer records are per-appointment-identity rather than per-person, so a common name returns many candidates and the appointment count and date of birth are usually what separates them.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	Yes	The officer's name.
`verbose`	No	Also return the untouched Companies House payload under `raw`, alongside the shaped result. Roughly two and a half times the size; use it only when a field you need is missing from the shaped result.
`start_index`	No	Zero-based offset into the full result set. Use pagination.has_more to decide.
`items_per_page`	No	How many records to return. Defaults to the API default; the maximum is 100.

Output Schema

TableJSON Schema

Name	Required	Description
`raw`	No	The untouched Companies House payload. Present only when verbose was true.
`meta`	Yes	Provenance and budget for this answer.
`query`	Yes
`officers`	Yes
`pagination`	Yes	Where this page sits in the full result set.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv0.4.0Sep 5, 2026

addedInput schema / properties / query / maxLength
```
Added value: +256
```

changedOutput schema / properties / meta / properties / licence / description

Previous value: -"Companies House data is Open Government Licence v3.0."New value: +"OGL v3.0 applies to eligible public-sector information. Personal data and other OGL exclusions are not licensed by this label; applicable data-protection duties still apply."

First observedv0.2.0Aug 30, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses a key behavioral quirk: officer records are per-appointment-identity rather than per-person, so common names return many candidates and appointment count plus date of birth separate them. This is exactly the kind of caveat an agent needs before invoking or interpreting results.

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?

Purpose is front-loaded in the opening sentence, followed by return values, usage guidance, and a caveat. Every sentence adds useful information and there is no padding or redundancy.

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?

Covers what the tool does, when to use it, what it returns, a key data-model caveat, and the downstream tool to call next. With a complete input schema and an output schema present, nothing essential is missing for correct selection and 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?

The input schema already describes all four parameters with 100% coverage, so the baseline is 3. The description adds no param-specific detail beyond 'by name', which the schema already conveys; it relies on the schema for parameter meaning.

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 the exact operation — 'Search Companies House for a company officer by name' — and scopes it to directors, secretaries, and LLP members. It also clarifies the output is candidate officer IDs with appointment counts, which distinguishes it from company search and officer-appointment retrieval tools.

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?

Gives an explicit usage condition: use it when you have a person and want the companies they are involved in, and names get_officer_appointments as the next step. It does not spell out when-not-to-use it versus siblings like get_officers, but the context is otherwise clear.

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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