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by ai.tulina.mcp
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apify_store_search

Read-only

Search Apify's public Store for an actor that already scrapes your target.

Start here: naming a target ("google maps reviews", "linkedin company", "amazon products") is how you find the actor to run, along with its pricing and its identifier.

Returns — {data: {items: [{id, username, name, title, description, stats, pricingInfos, …}], total}}. Run it with username/name.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "apify_store_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
_orgNoOrg (id) de CET APPEL. `oto_list_orgs()`.
limitNo
_groupNoÉquipe (id) de CET APPEL, sous son org parente.
searchNofree text describing the site or data you want.
_run_idNoOBLIGATOIRE à chaque appel dès `run_start` ou `data_claim_next` : sans lui, l'écriture sur une ligne réservée est refusée. Hérité seulement si le serveur tient un run actif — n'y compte pas.
sort_byNo`"relevance"` | `"popularity"` | `"newest"` | `"lastUpdate"`.
_projectNoProjet (id) de CET APPEL — jeton PRIMAIRE. `oto_project(op='list')`.
categoryNoStore category (e.g. `"SOCIAL_MEDIA"`, `"ECOMMERCE"`).
_instanceNoInstance de connecteur PRÉCISE (un credential exact). `oto_instance(op='list')`.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A3.8/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read, and the description is consistent with that. It adds useful behavior beyond the annotation by showing the return envelope and the key fields (id, username, name, stats, pricingInfos, total) and by noting that the returned identifier is what you feed to the run tool. It says nothing about result caps, pagination, or how relevance ordering affects results.

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?

Four short sentences, front-loaded with the action and the 'start here' cue, with no filler. The 'Returns —' block is slightly awkwardly formatted but carries dense, non-redundant information.

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?

For a nine-parameter but zero-required discovery search with no output schema, the description covers the action, the input phrasing, the return shape, and the handoff to execution. The remaining gaps are minor: nothing on the `limit` cap or on the tenant-scoping underscore parameters, though those are covered by the schema.

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 89%, so the baseline is 3 and most parameters are already documented. The description still adds real meaning by showing how the free-text `search` parameter should be phrased (a plain-language target like 'linkedin company') and by tying the returned `username/name` back to downstream use, which the schema does not do.

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 opening sentence gives a specific verb and resource — search Apify's public Store for an actor — and adds the qualifier 'that already scrapes your target', which is exactly the discovery framing an agent needs. It is not explicitly contrasted with the similarly named sibling apify_actors, so an agent still has to infer which of the two is the store lookup versus the actor listing.

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 phrase 'Start here' plus the concrete phrasing advice ('google maps reviews', 'linkedin company', 'amazon products') clearly establishes this as the first step before running anything. It does not name a when-not condition or point to apify_actors/apify_actor as the alternative for when the actor is already known.

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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