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VisiblyAI MCP Server

VisiblyAI MCP Server

by AntonioBlago
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

check_serp

Analyze live Google search results for any keyword. Identify top-ranking pages, dominant content types, and SERP features to inform competitive analysis and content gap detection.

Instructions

Check live Google SERP for a keyword. See who ranks, what content types dominate, and SERP features present.

Use for: competitive analysis, content gap detection, SERP intent analysis. Credits: 15.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keyword": "<keyword>"
    },
    "name": "check_serp"
  }
}

Input Schema

NameRequiredDescriptionDefault
depthNo
keywordYes
languageNoGerman
locationNoGermany

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. Mentions credits (15) and implies read-only operation via 'live Google SERP check', but lacks details on side effects, auth requirements, or rate limits.

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?

Two clear paragraphs: first states purpose, second lists use cases and credits. Efficient but could be more structured with parameter descriptions.

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?

Output schema exists, so return values not needed. Description covers key output aspects (ranks, content types, features). Lacks handling of edge cases like empty results.

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

Parameters1/5

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

Schema coverage is 0% and description does not explain any parameters (keyword, location, language, depth). No value added beyond the schema structure.

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 clearly states the tool checks live Google SERP for a keyword and specifies what information is provided (who ranks, content types, SERP features). It is specific and distinct from sibling tools like get_keywords or classify_keywords.

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?

Explicitly lists use cases: competitive analysis, content gap detection, SERP intent analysis. However, no guidance on when not to use or alternatives among siblings.

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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