Amplitude

Amp Get Events

amp_get_events

Read-onlyIdempotent

Get event counts and breakdowns for a date range (e.g., "2024-01-01" to "2024-01-31"). Returns frequency, user segments, and trends by event name.

Input Schema

TableJSON Schema

Name	Required	Description
`end`	Yes	End date (YYYYMMDD)
`start`	Yes	Start date (YYYYMMDD)
`_apiKey`	Yes	Amplitude API key
`group_by`	No	Property to group by (optional)
`_secretKey`	Yes	Amplitude secret key
`event_type`	Yes	EXACT event name as registered in the Amplitude project (case-sensitive). Do NOT guess or invent names — use the user-provided event name verbatim. Amplitude rejects unknown events with a 400.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No	Raw event data by time period
`series`	No	Event counts segmented by property

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedJun 22, 2026

changedInput schema / properties / event_type / description

Previous value: -"Event name to query (e.g., \"Page View\", \"Button Click\")"New value: +"EXACT event name as registered in the Amplitude project (case-sensitive). Do NOT guess or invent names — use the user-provided event name verbatim. Amplitude rejects unknown events with a 400."

Changed1 schema field changedMay 8, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "data": {
+      "description": "Raw event data by time period",
+      "type": "object"
+    },
+    "series": {
+      "description": "Event counts segmented by property",
+      "items": {
+        "properties": {
+          "segmentation_name": {
+            "description": "Segment value name",
+            "type": "string"
+          },
+          "segmentation_type": {
+            "description": "Segmentation dimension",
+            "type": "string"
+          },
+          "value": {
+            "description": "Event count for segment",
+            "type": "number"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

Changed1 schema field changedMay 6, 2026

addedInput schema / examples

Added value: +[
+  {
+    "_apiKey": "your-amplitude-api-key",
+    "_secretKey": "your-amplitude-secret-key",
+    "end": "20240131",
+    "event_type": "Page View",
+    "start": "20240101"
+  },
+  {
+    "_apiKey": "your-amplitude-api-key",
+    "_secretKey": "your-amplitude-secret-key",
+    "end": "20240122",
+    "event_type": "Button Click",
+    "group_by": "country",
+    "start": "20240115"
+  }
+]

First observedApr 22, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, destructiveHint, so the safety profile is covered. The description adds behavioral context (returns frequency, segments, trends) but does not go beyond what annotations already imply. No contradiction.

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?

Two sentences, front-loaded with purpose and examples. Every sentence adds value without redundancy. Appropriate length for the tool's complexity.

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 are covered. The description explains what is returned (frequency, user segments, trends) and date range. Minor gap: no mention of data freshness or latency, but overall complete for a read-only analytics tool.

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 coverage is 100%, so parameters are already well-documented. The description adds minimal extra semantic value beyond repeating date range format and event name. Examples in schema provide context, but description itself doesn't enhance beyond baseline.

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 it gets event counts and breakdowns for a date range, specifying return types (frequency, user segments, trends). This distinguishes it from sibling tools like amp_get_active_users or amp_get_retention, which focus on different analytics.

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?

The description provides clear context for when to use: to retrieve event metrics over a date range, with example dates. However, it does not explicitly exclude cases or mention alternative tools, leaving some guidance gap for agents.

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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