Mencoro

Sample AI mention texts

get_mention_samples

Read-onlyIdempotent

Paginated sample of the raw AI mention texts themselves, for qualitative review and verifying sentiment labels. Use to READ individual mentions. For the aggregate sentiment split use get_sentiment_breakdown; for the brand's own mention counts by type, tone and qualifier use get_mention_mix. Filterable by engine, sentiment, mention type and competitor. Dates must fall within the data retention window. limit is 1-50 (default 20). Answers questions like "show or export the actual AI mention texts" for a query.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`dateTo`	Yes
`offset`	No
`sortBy`	No		recent
`engines`	No	allowed values: chatgpt, claude, perplexity, google_ai_overview, google_ai_mode, google_serp, google_shopping
`dateFrom`	Yes
`countries`	No	ISO-3166 alpha-2 country codes (e.g. "US", "GB", "DE"); a project's configured codes are listed by get_available_filters
`projectId`	Yes
`sentiment`	No
`mentionType`	No
`competitorId`	No	UUID of a single competitor to filter to; competitor UUIDs are listed by get_available_filters (competitors[].id). Omit to include all competitors
`organizationId`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`total`	Yes
`samples`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 1, 2026

changedInput schema / properties / engines / description

Previous value: -"allowed values: chatgpt, perplexity, google_ai_overview, google_ai_mode, google_serp, google_shopping"New value: +"allowed values: chatgpt, claude, perplexity, google_ai_overview, google_ai_mode, google_serp, google_shopping"

changedInput schema / properties / engines / items / enum

Previous value: -[
-  "chatgpt",
-  "perplexity",
-  "google_ai_overview",
-  "google_ai_mode",
-  "google_serp",
-  "google_shopping"
-]New value: +[
+  "chatgpt",
+  "claude",
+  "perplexity",
+  "google_ai_overview",
+  "google_ai_mode",
+  "google_serp",
+  "google_shopping"
+]

addedOutput schema / properties / samples / items / properties / citations

Added value: +{
+  "description": "Sources the engine cited, in the order it cited them",
+  "items": {
+    "description": "A source cited inside one AI answer",
+    "properties": {
+      "anchorText": {
+        "description": "The visible link text, when the engine provided one",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "domain": {
+        "description": "Host of url. Belongs to the redirector, not the publisher, when unresolved is true",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "position": {
+        "description": "Place within this answer, starting at 1",
+        "minimum": 1,
+        "type": "integer"
+      },
+      "publicationDate": {
+        "description": "Publication date the engine reported, when it provided one",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "snippet": {
+        "description": "Excerpt the engine showed for this source, when it provided one",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "sourceName": {
+        "description": "Publisher name the engine reported, when it provided one",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "thumbnailUrl": {
+        "description": "Preview image the engine showed for this source, when it provided one",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "title": {
+        "description": "Title of the cited page, when the engine provided one",
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "unresolved": {
+        "description": "True when url still points at a redirector: count the citation, do not attribute the domain",
+        "type": "boolean"
+      },
+      "url": {
+        "description": "The URL exactly as the engine cited it, redirector included when unresolved is true",
+        "type": "string"
+      }
+    },
+    "required": [
+      "url",
+      "position",
+      "unresolved"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}

Changed10 schema fields changedSep 17, 2026
- addedInput schema / properties / competitorId / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
```
- removedInput schema / properties / competitorId / type
```
Removed value: -[
-  "null",
-  "string"
-]
```
- addedInput schema / properties / mentionType / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
```
- removedInput schema / properties / mentionType / type
```
Removed value: -[
-  "null",
-  "string"
-]
```
- addedInput schema / properties / sentiment / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
```
- removedInput schema / properties / sentiment / type
```
Removed value: -[
-  "null",
-  "string"
-]
```
- addedOutput schema / properties / samples / items / properties / competitorId / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
```
- removedOutput schema / properties / samples / items / properties / competitorId / type
```
Removed value: -[
-  "string",
-  "null"
-]
```
- addedOutput schema / properties / samples / items / properties / mentionPosition / anyOf
```
Added value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
```
- removedOutput schema / properties / samples / items / properties / mentionPosition / type
```
Removed value: -[
-  "integer",
-  "null"
-]
```
First observedSep 15, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive behavior, so the safety profile is covered. The description still adds real value beyond them: the data retention window constraint on dates and the limit range (1-50, default 20), which annotations cannot express.

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?

Front-loaded with what the tool returns, then alternatives, then filters. Dense but mostly earns its place; the trailing 'Answers questions like...' sentence is mildly redundant with the opening statement.

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 need no explanation, and the retention-window and pagination constraints are disclosed. Only gap is the absence of guidance on sortBy and offset semantics for a 12-parameter tool, which is minor given the structured coverage.

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 only 25% across 12 parameters, so the description must compensate. It does name the filterable dimensions (engine, sentiment, mention type, competitor) and the limit bounds, but it omits any meaning for sortBy, offset, and countries (which is in fact a filter too). Partial compensation, not full.

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?

States a specific verb and resource: a paginated sample of raw AI mention texts for qualitative review and sentiment-label verification. It explicitly names and distinguishes itself from siblings get_sentiment_breakdown and get_mention_mix.

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

Usage Guidelines5/5

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

Give explicit routing: 'Use to READ individual mentions', then names the aggregate alternative (get_sentiment_breakdown) and the count-by-type/tone alternative (get_mention_mix). The when-to-use decision is fully resolved without opening sibling schemas.

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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