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yandex-api-mcp

yandex-api-mcp

by 5iNeX
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

direct.list_adextensions

Retrieve ad extensions from Yandex Direct with pagination and optional selection criteria, so you can review or manage extension data by account.

Instructions

List ad extensions.

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": "direct.list_adextensions"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPagination: {"limit": int, "offset": int}.
paramsNoRaw Direct params override (advanced).
account_idNoProject profile id (resolves to Direct Client-Login and optional Metrica counter defaults).
field_namesNoAd extension field names (default: Id).
selection_criteriaNoDirect API SelectionCriteria object (optional).
direct_client_loginNoOverride Direct Client-Login for this call (agency multi-project support).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it delivers essentially none. It does not state that the operation is read-only, what a returned extension looks like, how pagination behaves, or that account_id/direct_client_login are needed for auth resolution.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single front-loaded sentence with zero padding, which is structurally fine. However, it is under-specified rather than genuinely concise – there is no second sentence of value to trim, so brevity here reflects missing information, not discipline.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters, nested objects, no output schema, and no annotations, the definition should explain the read-only nature, pagination semantics, and account/profile resolution. A one-line description leaves an agent without enough context to call this correctly in a large multi-tool environment.

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 the schema already documents every parameter, including pagination, field_names, selection_criteria, and the raw params override. The description adds nothing beyond the schema, which is the expected baseline when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a clear verb+resource ("List ad extensions"), so an agent knows the basic action. But it does nothing to distinguish this tool from the many other list siblings such as direct.list_sitelinks, direct.list_vcards, or direct.list_bids, so the purpose is only minimally viable.

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

Usage Guidelines2/5

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

There is no statement of when to use this tool, no prerequisites, and no routing to alternatives. An agent must infer usage entirely from the resource name, which is exactly the gap that causes wrong-tool selection among the crowded direct.list_* family.

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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