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lexdoudkin

handelsregister-mcp

by lexdoudkin

fetch_document

Search for a company in the German Commercial Register by keywords, select a document type, and retrieve the extracted text from the downloaded PDF or XML.

Instructions

Retrieve a register document/extract for a company and return its text.

Runs a search, picks result_index from the hits, then downloads the requested document type from that same portal session. Document types: AD - current extract CD - chronological extract HD - historical extract DK - filed documents register SI - structured XML data VÖ - announcements UT - holder data

Returns the local file path, content_type, size_bytes, and (for PDF/XML) extracted text. Document retrieval is the most fragile part of the portal flow; if it fails, the error explains what happened.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYes
document_typeNoAD
matchNoexact
result_indexNo
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses that document retrieval is 'the most fragile part of the portal flow' and that errors explain what happened. It also outlines the steps (search, pick index, download) and document types. This adds behavioral context beyond a simple read operation, though it could mention if auth or rate limits apply.

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 well-structured with front-loaded purpose, a clear step-by-step process, and a bulleted list of document types. It is informative without being overly verbose, earning its sentences. Minor redundancy in the first sentence (repeats 'document/extract') but overall efficient.

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?

Given no output schema, the description explains return fields (path, content_type, size_bytes, text) and addresses fragility. It covers the search-to-download flow and document types. For a tool with 4 parameters and a moderate complexity, this provides sufficient completeness, though sibling differentiation 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 coverage is 0%, so the description must compensate. It adds meaning to 'keywords' (used for search), 'result_index' (picked from hits), and 'document_type' (lists options), but does not explain the 'match' parameter. The description provides context but is not fully comprehensive for all 4 parameters.

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 states the tool retrieves a register document/extract for a company and returns its text. It specifies the process: runs a search, picks a result index, downloads the document type. While the purpose is specific and distinct from generic document fetching, it does not explicitly differentiate from the sibling tool 'fetch_filed_document', which overlaps in functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through the document types and fragility warning, but it does not explicitly state when to use this tool versus alternatives like fetch_filed_document. No exclusions or prerequisites are mentioned, leaving the agent to infer use cases.

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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