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kaylum54

companies-house-screening-mcp

by kaylum54

Get charges

get_charges
Read-onlyIdempotent

Retrieve a company's registered charges: holders, coverage, creation, and satisfaction. Outstanding count flags unresolved secured debt for supplier or debtor screening. Needs a company number.

Instructions

Secured debt registered against a company: who holds each charge, what it covers, when it was created and whether it has been satisfied. outstanding_count is derived here because Companies House reports what has been settled but never what has not, and outstanding charges are the number that matters when screening a supplier or a debtor. A floating charge covering all assets is worth reading closely. Needs a company number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
verboseNoAlso 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.
company_numberYesEight-character Companies House number, such as 00000006 or SC123456. Leading zeros may be omitted. This tool does not accept a company name — call find_company first if that is all you have.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoThe untouched Companies House payload. Present only when verbose was true.
metaYesProvenance and budget for this answer.
chargesYes
total_countYes
company_numberYes
satisfied_countYes
outstanding_countYesDerived: total minus satisfied and part-satisfied.
part_satisfied_countYes
Install Server

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses that outstanding_count is derived because Companies House never reports what has not been settled, and it flags floating charges as worth close reading. This adds genuinely useful behavioral and interpretive context that annotations do not 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 short and every sentence carries information: what the tool returns, why outstanding_count is derived, and what to watch for in floating charges. The company-number prerequisite is placed at the end rather than up front, and the opening is a noun phrase, but overall it is well-structured and free of filler.

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 an output schema present and annotations covering read-only and idempotent behavior, the description provides enough context for correct invocation: the purpose, prerequisite, derived field, and a screening use case. It lacks explicit sibling differentiation, which is the main gap preventing a 5.

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 both parameters are already well documented. The description mostly restates the company-number requirement and adds no new format or behavior details beyond the schema, which puts it at the baseline 3.

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 clearly names the resource — secured debt/charges registered against a company — and lists the key data returned: holder, coverage, creation date, and satisfaction status. It does not use an explicit verb like 'retrieves' or 'lists,' but the meaning is unmistakable and distinct from sibling company-data 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?

It gives clear context for when this tool matters — screening a supplier or debtor — and states the key prerequisite of needing a company number. It does not explicitly name alternatives or say when not to use it, so it stops short of a 5.

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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