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AIWerk

@aiwerk/mcp-server-swiss-company

Official
by AIWerk

ch_company_search

Read-only

Find Swiss companies by registered name or statutory purpose. Returns UID, legal form, address, and purpose to verify the right match.

Instructions

Find Swiss companies in the commercial register by part of their registered name, or by a word in their statutory purpose (match="purpose", needs a canton). Returns candidates with UID, legal form, address and purpose. The name match is a substring of the registered name, so a name from a website or Google Maps may need a shorter, distinctive part. When several candidates come back, confirm the right one by address before using its UID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum candidates, default 20.
matchNo"name" (default) searches registered names, "purpose" searches the statutory purpose.
queryYesText to look for. With match="name" (default), part of the registered company name, e.g. "Muster Treuhand". With match="purpose", a word from the statutory purpose, e.g. "Buchführung".
cantonNoTwo-letter canton code such as BE or ZH. Required for match="purpose".
legal_formNoAG, GmbH, Einzelunternehmen, Genossenschaft, Verein, Stiftung, or an eCH-0097 code such as 0106.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the tool read-only and open-world; the description adds useful behavioral detail beyond that, such as the substring behavior, the canton requirement for purpose searches, and the advice to confirm candidates by address. It does not disclose every edge case or rate limit, but the added context is meaningful for correct use.

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 compact, front-loaded with the core purpose, and every sentence earns its place: search behavior, returned fields, substring caveat, and disambiguation advice. No redundant filler or restatement of obvious schema details.

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?

Despite having no output schema, the description explains what results contain and how to handle ambiguous results. The schema fully documents the five parameters, and annotations cover the safety profile. Nothing essential for an agent to decide when to call this tool is missing.

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 baseline is 3. The description adds a small amount of real-world guidance, such as using a shorter, distinctive name fragment and confirming by address, but it largely restates parameter information already present in the schema, especially for query, match, and canton.

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 opens with a specific verb and resource ('Find Swiss companies in the commercial register') and clearly distinguishes the two search modes: by registered name or by statutory purpose. It names the returned entity fields, which lets an agent separate this search tool from sibling tools like ch_company_profile or ch_validate_uid.

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?

The description provides clear use context: name matching is substring-based, purpose matching requires a canton, and results should be disambiguated by address before using a UID. It does not explicitly contrast this tool with sibling alternatives, but the intended workflow is evident from the concrete guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.