Veqen: AI cost monitoring and protection

Get a model's price

get_model_price

Read-onlyIdempotent

Rates for one model of any kind. Token rates are USD per million tokens: input (in), output (out), cache read (cr), cache write (cw, cw1h) and audio (ain, aout), with batch, priority and long-context tiers. Models billed per image, second, character, query or page have a unit rate (unit), and may have size, quality or resolution variants (v:...).

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": {
      "model": "<model>"
    },
    "name": "get_model_price"
  }
}

Input Schema

Name	Required	Description	Default
`model`	Yes	Model id as you'd pass it to the API: gpt-4o-mini, Qwen/Qwen3.5-9B, fal-ai/flux/dev
`provider`	No	Provider key, such as openai, together, bedrock, fal or deepgram

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description adds real context beyond that: rates are USD per million tokens, the field abbreviations (in, out, cr, cw, cw1h, ain, aout), tiering (batch, priority, long-context), and the unit-rate variant scheme for non-token billing.

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, front-loaded with the core statement, then a dense but necessary glossary of rate fields and tiers. No filler.

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 values needn't be spelled out, yet the description still decodes the rate fields and variant notation. Only the relationship to sibling pricing tools is unaddressed.

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 coverage is 100%, so both model and provider are already documented in the schema. The description adds only a general note that any model kind is supported, which is the correct baseline when the schema does the heavy lifting.

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 resource and outcome — pricing rates for a single model — and the sentence 'Models billed per image, second, character, query or page have a unit rate' makes the scope (any model kind) explicit. It does not name siblings like compare_models or list_models, so differentiation is left to inference.

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?

There is no when-to-use guidance, no prerequisites, and no named alternative. An agent must infer from the sibling list that compare_models handles multi-model comparison while this returns rates for one model.

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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