AICostBudget AI API Pricing

Estimate monthly cost

estimate_monthly_cost

Read-onlyIdempotent

Calculate projected monthly AI API token costs from request volume. Include cached input ratios and batch pricing to budget accurately.

Instructions

Estimate monthly token cost from request volume, with optional cached-input and batch pricing.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`model`	Yes
`use_batch`	No
`cached_input_ratio`	No
`requests_per_month`	Yes
`input_tokens_per_request`	Yes
`output_tokens_per_request`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes
`source`	Yes
`verified_at`	Yes
`aicostbudget_url`	Yes
`bundled_fallback`	Yes
`official_source_urls`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds useful context that caching and batch pricing modes affect the result, but says nothing about assumptions (e.g., cached ratio defaults) or output shape.

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?

A single front-loaded sentence with the primary action first and the optional pricing modes trailing. No filler or redundant restatement of the title.

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?

An output schema exists, so return-value explanation is unnecessary, and annotations cover behavior. The description is adequate for a 6-parameter estimation tool, though it leaves the sibling-selection question unanswered.

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 0%, so the description must carry the load. It loosely maps to the parameters (request volume, cached-input, batch pricing) but omits units, formats, and the model parameter entirely, so it only partially compensates.

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?

Clear specific verb (estimate) plus resource (monthly token cost) and the driving input (request volume), with optional pricing modes called out. It does not differentiate itself from siblings like get_model_price or compare_models, but the core purpose is unambiguous.

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

Usage Guidelines2/5

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

No when-to-use, prerequisites, or alternatives are given. An agent cannot tell from this text whether to reach for this versus get_model_price for a single-model lookup or compare_models for a side-by-side. Usage is only implied by the verb 'estimate'.

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

Deploy Server