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Api Serp Yandex

api_serp_yandex

Yandex SERP for RU-market keyword research (region by ?lr=). ?q=&lr=213 [HTTP x402 price: $0.01]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / params / additionalProperties
      Removed value: -true
    • addedInput schema / properties / params / properties
      Added value: +{
      +  "lr": {
      +    "anyOf": [
      +      {
      +        "type": "string"
      +      },
      +      {
      +        "type": "null"
      +      }
      +    ],
      +    "default": null
      +  },
      +  "q": {
      +    "anyOf": [
      +      {
      +        "type": "string"
      +      },
      +      {
      +        "type": "null"
      +      }
      +    ],
      +    "default": null
      +  }
      +}
  2. First observed

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It discloses the region parameter via ?lr= and mentions pricing/cost, but it does not state whether results are live, what result types are returned, whether auth is needed, or that this is a read-only operation. This is a meaningful transparency gap for a SERP tool.

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 compact and front-loaded with the core purpose. It includes a useful example and cost hint without wasted words, though the 'HTTP x402 price' phrasing is somewhat cryptic.

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

Completeness3/5

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

The tool has an output schema and only two optional parameters, so the description does not need to explain return structure. Still, it is missing explicit guidance on when to choose Yandex over Google SERP, and it leaves parameter semantics partly implicit. It is adequate for a simple tool but not fully self-sufficient.

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 0%, so the description must compensate. It does partially: ?q= indicates the keyword query and ?lr=213 indicates region by Yandex region code. However, it does not explain the expected value format for lr beyond the example, nor the optional/default behavior of q and lr.

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 identifies the resource as Yandex SERP and the use case as RU-market keyword research. It distinguishes itself from the sibling api_serp_google by naming Yandex and the RU-market focus, though it lacks an explicit verb like 'get' or 'retrieve'.

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 RU-market and Yandex framing implies when this tool is appropriate, but it never explicitly contrasts it with api_serp_google, api_search, or other siblings. Usage context is present, but exclusions and alternative-selection rules are left to inference.

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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