AI Admin API MCP Server

ai_admin_query_usage

Read-only

Query normalized usage facts from enabled AI providers. Pass provider-specific options to filter data by date range and provider.

Instructions

Query normalized usage facts from one or more enabled providers. Pass provider-specific options under provider_options[provider_id].

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "start": "<start>",
      "end": "<end>"
    },
    "name": "ai_admin_query_usage"
  }
}

Input Schema

Name	Required	Default
`end`	Yes
`start`	Yes
`providers`	No
`include_raw`	No
`bucket_width`	No	1d
`credential_refs`	No
`provider_options`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.1Aug 1, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safe read-only nature is covered. The description adds context about passing provider-specific options via provider_options[provider_id], but does not disclose rate limits, pagination, or return format.

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, each earning its place. The first states the purpose; the second gives a direct usage tip. No redundant wording or filler.

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

Completeness2/5

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

Given the tool's complexity (7 parameters, nested objects, no output schema), the description is too sparse. It omits critical context about the date range, provider selection, raw data inclusion, bucket widths, credential references, and expected response shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only explains provider_options. The other six parameters (start, end, providers, include_raw, bucket_width, credential_refs) remain completely undocumented, leaving the agent without guidance on their meaning or usage.

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 the verb 'Query' and the resource 'normalized usage facts' from 'one or more enabled providers', which is specific and distinguishes it from sibling tools like query_costs and query_dashboard_bundle.

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

Usage Guidelines3/5

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

The description implies its use for querying usage data but does not explicitly contrast it with alternatives or state when not to use it. No exclusions or alternative tool references are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server