GEO MCP by DigestSEO

Get AI visibility history

get_visibility_history

Read-only

Get daily or weekly brand visibility history with per-engine evidence to monitor AI citations across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.

Instructions

Return daily or weekly visibility history with per-engine evidence. Example: brand_id='acme', days=30, granularity='weekly'.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	Previous calendar days to include.
`brand_id`	Yes	Tracked brand ID to inspect.
`granularity`	No	Time bucket for the series.	weekly

Output Schema

TableJSON Schema

Name	Required	Description	Default
`days`	Yes
`series`	Yes
`brand_id`	Yes
`granularity`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.3.23Sep 23, 2026

changedInput schema / properties / brand_id / description

Previous value: -"Stable identifier of the tracked brand to inspect."New value: +"Tracked brand ID to inspect."

changedInput schema / properties / days / description

Previous value: -"Number of previous calendar days to include."New value: +"Previous calendar days to include."

changedInput schema / properties / granularity / description

Previous value: -"Time bucket for the returned visibility series."New value: +"Time bucket for the series."

Changed2 schema fields changedv0.3.15Sep 20, 2026

addedOutput schema / properties / series / items / properties / per_engine_evidence

Added value: +{
+  "additionalProperties": {
+    "additionalProperties": false,
+    "properties": {
+      "brand_mentions": {
+        "type": "number"
+      },
+      "observed_at": {
+        "type": "string"
+      },
+      "usable_prompts": {
+        "type": "number"
+      }
+    },
+    "required": [
+      "brand_mentions",
+      "usable_prompts",
+      "observed_at"
+    ],
+    "type": "object"
+  },
+  "propertyNames": {
+    "type": "string"
+  },
+  "type": "object"
+}

changedOutput schema / properties / series / items / required

Previous value: -[
-  "date",
-  "overall_score",
-  "per_engine"
-]New value: +[
+  "date",
+  "overall_score",
+  "per_engine",
+  "per_engine_evidence"
+]

First observedv0.3.2Aug 3, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about per-engine evidence and granularity but does not disclose behaviors like pagination, date handling, or potential lack of data coverage.

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 two terse sentences with no filler. The functional statement and example are both valuable, and the example is compact enough to aid understanding without bloating the description.

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?

For a simple read-only query with full schema documentation, an output schema, and safety annotations, the description is nearly sufficient. The main missing element is explicit sibling differentiation for when to call this instead of check_visibility, but the example and function statement cover correct invocation.

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 input schema already documents all three parameters. The example maps brand_id, days, and granularity to concrete values, which is helpful illustration, but it does not add meaning beyond what the schema and enum definitions provide.

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 states a specific verb ('Return') and resource ('daily or weekly visibility history with per-engine evidence'), making the basic action unambiguous. It does not explicitly distinguish itself from the sibling check_visibility, but the 'history' framing and granularity options provide enough differentiation.

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 guidance on when to use this tool versus alternatives like check_visibility or compare_competitors. The example shows how to invoke it but gives no exclusions, prerequisites, or context for choosing this tool over related 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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