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BORME API - Spain company registry

brand_owner

Find the Spanish company a brand or trading name is linked to, by holder name.

Searches the patent office's trademarks and commercial names (1987 to today), which BORME does not print, and returns for each the company whose name matches the holder name the office published.

commercial_name identifies a business; trademark distinguishes goods or services (NESCAFÉ is not another name for Nestlé). Say which kind a hit is; do not say a company "is called" X when X is one of its products.

Links are made on a normalised company name only (the office publishes no tax IDs) and only where exactly one company or registry sheet fits: present a hit as a name match, not confirmed ownership. On a hit, use company_history with the slug.

Needs the basic plan or higher: send your API key in the X-API-Key header (https://bormeapi.com/account).

Input Schema

NameRequiredDescriptionDefault
brandYesBrand or trading name, or part of it.
limitNoMaximum results, 1-200 (default 20).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well. It discloses the data source and date range, normalised-name-only matching, absence of tax IDs, the rule that only exactly one company/registry sheet may fit, that hits are name matches rather than confirmed ownership, and the API plan/header requirement.

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 front-loaded with the core purpose and then adds the important matching and authentication caveats. It is somewhat dense but each sentence contributes useful guidance, with no obvious repetition.

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 tool with two parameters, no output schema, and no annotations, the description provides enough context to call it correctly. It covers data scope, matching limitations, how to interpret a hit, next-step guidance, and authentication requirements.

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 coverage is already 100%, so the baseline is 3. The description adds meaningful semantics for `brand`: it can be a commercial name identifying a business or a trademark distinguishing goods/services, and matching is by normalised holder name rather than tax ID.

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 states a specific verb and resource: find the Spanish company linked to a brand or trading name by holder name. It also distinguishes commercial names from trademarks and explains the patent-office data source, making the tool’s function clear.

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 clearly explains when the tool is useful: BORME does not print these trademark/commercial-name records, and on a hit the agent should use company_history. It does not explicitly compare against sibling company_brands, but the intended use 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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