portkey-admin-mcp

get_users_analytics

Read-onlyIdempotent

Analyze user-growth trends by retrieving time-series data with total and per-bucket counts of active and new users. Use it to track adoption and growth over a specified period.

Instructions

Get user-growth time-series data with summary.total_active_users, summary.total_new_users, and per-bucket active/new user counts. Use this for growth and adoption trends; use get_user_requests_analytics for per-user traffic or get_analytics_group_users for per-user cost and token detail. Enterprise-gated. Returns 403 on non-Enterprise Portkey plans.

Input Schema

TableJSON Schema

Name	Required	Description
`configs`	No	Legacy Portkey query param for config slugs. Comma-separated string; prefer config_slugs for structured inputs.
`span_id`	No	Legacy Portkey query param for span IDs. Comma-separated string; prefer span_ids for structured inputs.
`cost_max`	No	Maximum cost in cents to filter by
`cost_min`	No	Minimum cost in cents to filter by
`metadata`	No	Legacy Portkey query param for metadata filtering. Stringified JSON object, e.g. '{"env":"prod","app":"myapp"}'; prefer metadata_filter for structured inputs.
`span_ids`	No	Structured alias for span_id. Use an array of span IDs; normalized to the legacy comma-separated Portkey query param.
`trace_id`	No	Legacy Portkey query param for trace IDs. Comma-separated string; prefer trace_ids for structured inputs.
`trace_ids`	No	Structured alias for trace_id. Use an array of trace IDs; normalized to the legacy comma-separated Portkey query param.
`api_key_ids`	No	Legacy Portkey query param for API key UUIDs. Comma-separated string; request_analytics also accepts an array and normalizes it to this form.
`prompt_slug`	No	Filter by prompt slug
`status_code`	No	Legacy Portkey query param for HTTP status codes. Comma-separated string; prefer status_codes for structured inputs.
`ai_org_model`	No	Legacy Portkey query param for provider/model pairs. Format: 'provider__model' with double underscore, e.g. 'openai__gpt-4' or 'anthropic__claude-3-opus'. Comma-separated string; prefer provider_models for structured inputs.
`config_slugs`	No	Structured alias for configs. Use an array of config slugs; normalized to the legacy comma-separated Portkey query param.
`status_codes`	No	Structured alias for status_code. Use an array of HTTP status codes; normalized to the legacy comma-separated Portkey query param.
`virtual_keys`	No	Legacy Portkey query param for virtual key slugs. Comma-separated string; prefer virtual_key_slugs for structured inputs.
`workspace_slug`	No	Filter by specific workspace
`metadata_filter`	No	Structured alias for metadata. Use an object such as { env: 'prod' }; normalized to a JSON string before the request is sent.
`provider_models`	No	Structured alias for ai_org_model. Use provider__model strings in an array; normalized to the legacy comma-separated Portkey query param.
`total_units_max`	No	Maximum number of total tokens to filter by
`total_units_min`	No	Minimum number of total tokens to filter by
`prompt_token_max`	No	Maximum number of prompt tokens
`prompt_token_min`	No	Minimum number of prompt tokens
`virtual_key_slugs`	No	Structured alias for virtual_keys. Use an array of virtual key slugs; normalized to the legacy comma-separated Portkey query param.
`completion_token_max`	No	Maximum number of completion tokens
`completion_token_min`	No	Minimum number of completion tokens
`weighted_feedback_max`	No	Maximum weighted feedback score (-10 to 10)
`weighted_feedback_min`	No	Minimum weighted feedback score (-10 to 10)
`time_of_generation_max`	Yes	End time for the analytics period (ISO8601 format, e.g., '2024-02-01T00:00:00Z')
`time_of_generation_min`	Yes	Start time for the analytics period (ISO8601 format, e.g., '2024-01-01T00:00:00Z')

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	Whether the tool call succeeded and returned structured data
`data`	No	Structured success payload when ok is true
`error`	No	Structured error payload when ok is false

Schema Changelog

Changes observed during successful MCP inspections.

Changed16 schema fields changedv0.11.5Sep 8, 2026
- removedInput schema / properties / completion_token_max / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / completion_token_max / minimum
```
Added value: +0
```
- removedInput schema / properties / completion_token_min / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / completion_token_min / minimum
```
Added value: +0
```
- removedInput schema / properties / cost_max / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / cost_max / minimum
```
Added value: +0
```
- removedInput schema / properties / cost_min / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / cost_min / minimum
```
Added value: +0
```
- removedInput schema / properties / prompt_token_max / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / prompt_token_max / minimum
```
Added value: +0
```
- removedInput schema / properties / prompt_token_min / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / prompt_token_min / minimum
```
Added value: +0
```
- removedInput schema / properties / total_units_max / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / total_units_max / minimum
```
Added value: +0
```
- removedInput schema / properties / total_units_min / exclusiveMinimum
```
Removed value: -0
```
- addedInput schema / properties / total_units_min / minimum
```
Added value: +0
```

Changed1 schema field changedv1.0.2Jul 4, 2026

changedInput schema / required

Previous value: -[
-  "time_of_generation_min",
-  "time_of_generation_max",
-  "api_key_ids"
-]New value: +[
+  "time_of_generation_min",
+  "time_of_generation_max"
+]

Addedv1.0.1May 7, 2026
RemovedMay 1, 2026
First observedJan 1, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description adds value by disclosing the Enterprise gating requirement and the 403 error on non-Enterprise plans. It also clarifies the time-series output shape, which is useful beyond the annotations.

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?

Three tightly packed sentences: the first states what is returned, the second routes to alternatives, and the third notes the Enterprise gating and error behavior. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the high parameter count and complexity, the description covers purpose, usage boundaries, output nature, and an important error condition. The schema covers parameter details and the output schema covers return values, so nothing critical is missing.

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 all 29 parameters are already fully documented in the input schema. The description adds no parameter-specific semantics, which is acceptable because the schema carries that burden completely.

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 states a specific verb ('Get user-growth time-series data') and names the exact resource and output fields (summary.total_active_users, summary.total_new_users, per-bucket counts). It also distinguishes itself from nearby siblings by name, so an agent can select it correctly without inspecting schemas.

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?

The description explicitly says to use it for growth and adoption trends and directs agents to get_user_requests_analytics for per-user traffic and get_analytics_group_users for per-user cost/token detail. It also discloses Enterprise-gating, eliminating ambiguity about when it can be used.

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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