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google-seo-mcp

by Akxan
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TypeScript
Hybrid

Entity presence: Google Knowledge Graph + Wikidata

knowledge_graph_check
Read-onlyIdempotent

Check if a brand, business, or place exists as an entity in Wikidata and Google Knowledge Graph. If missing, get steps to create one for better AI and Google recognition.

Instructions

Check whether a brand/business/place exists as an entity in Wikidata (free, no key) and in Google's Knowledge Graph Search API (needs the 'Knowledge Graph Search API' enabled on the GCP project and a key in GOOGLE_API_KEY or PAGESPEED_API_KEY). AI engines and Google rely on entities to know 'who' a site is; if none exists, the result includes the steps to establish one. Narrow a generic heritage or place name with types, or pass ids to follow one known entity over time instead of searching by name again.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoLook up known Knowledge Graph entity ids instead of searching by name, e.g. ['kg:/m/02_286'] as printed by a previous run (the 'kg:' prefix is stripped automatically). Tracks the same entity over time without re-matching the name.
nameYesEntity name, e.g. 'Altai Turismo' or 'Casa Sefardí de Sevilla'.
limitNo
typesNoRestrict Knowledge Graph hits to these schema.org types, e.g. ['Organization','Place','TouristAttraction'] - the fastest way to cut the noise around a generic monument or town name.
languagesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.10.0
    • addedInput schema / properties / ids
      Added value: +{
+  "description": "Look up known Knowledge Graph entity ids instead of searching by name, e.g. ['kg:/m/02_286'] as printed by a previous run (the 'kg:' prefix is stripped automatically). Tracks the same entity over time without re-matching the name.",
+  "items": {
+    "type": "string"
+  },
+  "maxItems": 10,
+  "type": "array"
+}
    • addedInput schema / properties / types
      Added value: +{
+  "description": "Restrict Knowledge Graph hits to these schema.org types, e.g. ['Organization','Place','TouristAttraction'] - the fastest way to cut the noise around a generic monument or town name.",
+  "items": {
+    "type": "string"
+  },
+  "maxItems": 10,
+  "type": "array"
+}
  2. Changed1 schema field changedv0.5.1
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv0.3.0

TDQS

A4.6/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond the readOnly/openWorld/idempotent annotations: Wikidata needs no key, Google KG requires a specific GCP API and environment key, the 'kg:' prefix is stripped automatically, and the result includes establishment steps when no entity exists. This helps the agent understand authentication dependencies and side-effect-free behavior.

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 dense but every sentence earns its place: purpose, authentication requirements, the reasoning behind entities, and invocation tips. It is front-loaded with the main verb and resource, and nothing is wasted.

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?

The definition covers purpose, auth requirements, parameter strategy, and a key behavior (steps to establish an entity). It does not describe the expected output shape in detail, which would be useful since there is no output schema, but the core information needed to call the tool correctly is present.

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?

With 60% schema coverage, the description compensates by explaining key parameters: it tells the agent to use 'types' to narrow generic names and to pass 'ids' to track a known entity over time. The remaining parameters (limit, languages) are not covered in the description, but their names, defaults, and constraints in the schema make their roles reasonably clear.

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 opens with 'Check whether a brand/business/place exists as an entity in Wikidata ... and in Google's Knowledge Graph Search API,' which is a specific verb plus clear resources and scope. It also explains the broader purpose ('AI engines and Google rely on entities'), making it easy to distinguish from other tools in the large sibling list.

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?

It gives clear context about when to use the tool: to verify entity existence and to get steps to establish one if missing. It also gives practical guidance on narrowing generic names with types or following known IDs over time, though it does not explicitly name alternative tools or state when not to use this tool.

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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