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IIxauII

kleinanzeigen-mcp

by IIxauII

Find shops

find_shop
Read-only

Resolve a commercial seller's name to a shop slug on kleinanzeigen.de via live directory search. Verify the match before use, as it may come from profile text.

Instructions

Shop slugs for COMMERCIAL sellers matching a name. Makes a live request, unlike the other resolvers. A match may be a mention in a shop's profile text rather than its name, so check before using one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe commercial seller's name, passed to the directory's full-text search unchanged.
pageNo
category_idNo
location_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYes
countYes
staleYes
matchesYes
page_sizeYes
fetched_atYes
source_urlYes
stale_reasonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description adds meaningful behavioral details: the request is live/network-dependent, and matches may be loose profile-text mentions rather than exact name hits. This helps the agent set expectations about latency and result accuracy.

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 three sentences with no filler. It front-loads the core purpose, then adds the live-request differentiator and the important matching caveat. Every sentence adds necessary operational or behavioral value.

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 the output schema exists and annotations already signal safety/open-world expectations, the description covers the critical caveats: live request behavior and the possibility of profile-mention matches. It could be more complete by explaining the optional filter parameters, but the overall context is sufficient for correct invocation in most cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25%, and the description only meaningfully covers the 'name' parameter by stating it is passed to full-text search unchanged. The 'page', 'category_id', and 'location_id' parameters receive no explanation in either the schema or the description, so the agent has to infer their semantics from names alone.

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 exactly what the tool returns ('Shop slugs for COMMERCIAL sellers matching a name') and clearly distinguishes it from sibling resolvers by noting it 'makes a live request, unlike the other resolvers.' This tells the agent both the resource and the query intent without ambiguity.

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 useful invocation context: it performs a live request rather than using cached resolver data, and it warns that matches may be mentions in profile text rather than actual shop names. It does not explicitly name alternative tools or give strict when-not-to-use conditions, but the context is clear enough for an agent to choose correctly.

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