portkey-admin-mcp

get_feedback_scores_analytics

Read-onlyIdempotent

Retrieve raw feedback-score distribution time-series with per-score buckets to analyze user sentiment mix. Requires an Enterprise Portkey plan.

Instructions

Get raw feedback-score distribution time-series data with per-score buckets. Use this to understand sentiment mix; use get_feedback_weighted_analytics for calibrated scores with weighting. 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

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds the enterprise entitlement gate and its concrete failure mode ('Returns 403 on non-Enterprise Portkey plans'). This is useful behavioral context beyond the structured annotations, though it doesn't describe output shape or rate limits.

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 three short sentences with no filler: the capability, the usage recommendation, and the enterprise gate are each stated once. Key differentiators are front-loaded before the alternative and error condition.

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?

For a 29-parameter analytics tool, the description supplies the essential selection context (raw vs weighted, sentiment mix, enterprise gate) while the schema fully documents every parameter and an output schema exists. Nothing needed for correct selection or calling 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 the baseline applies and the description does not need to restate parameters. It also adds no parameter-level detail beyond the schema; the only extra cue, 'per-score buckets,' relates to the output rather than the inputs.

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 a specific verb and resource: 'Get raw feedback-score distribution time-series data with per-score buckets.' This clearly identifies what the tool returns and the raw/per-score qualifiers distinguish it from the weighted feedback sibling without needing to inspect 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?

It gives explicit usage context: 'Use this to understand sentiment mix; use get_feedback_weighted_analytics for calibrated scores with weighting.' This tells the agent when to call this tool and names the exact alternative, satisfying the when/when-not requirement.

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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