LLM Pricing

get_pricing_history

Query historical pricing snapshots recorded over time. Use this to look up past prices for a model or provider, or to see how prices have changed over a given number of days.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_pricing_history"
  }
}

Input Schema

Name	Required	Description
`days`	No	Look-back window in days (default: 30, max: 365)
`limit`	No	Maximum number of snapshot rows to return (default: 50, max: 500)
`provider`	No	Filter by provider (e.g. 'openai'). Omit for all providers.
`model_name`	No	Filter by model name (e.g. 'gpt-4o'). Omit for all models.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It conveys that this is a read-only lookup of recorded data, but says nothing about result volume behavior (limit/max 500), whether older snapshots may be missing, or auth needs. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, purpose first then usage, no filler. 'Recorded over time' is mildly redundant with 'historical', keeping it just below perfect.

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 tool with no output schema, no required parameters and fully documented properties, the description covers what the tool returns at a conceptual level and when to reach for it. Only return-shape and pagination cues are absent.

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%, with defaults, min/max and example values for every parameter, so the baseline is 3. The description only loosely gestures at the days window and provider/model filtering without adding format or combination semantics.

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?

States a specific verb and resource: query historical pricing snapshots. The word 'historical' and 'recorded over time' implicitly separate it from siblings like get_all_pricing (current prices) or check_price_drift, though no sibling is named explicitly.

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?

Gives clear usage contexts: look up past prices for a model or provider, or see price changes over a number of days. Missing explicit when-not guidance or a named alternative (e.g. get_pricing_trends for trend analysis), so it stops short of a 5.

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

All LLM Pricing tools Inspect

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