Skip to main content
Glama
Sign In
claude-cost-mcp

claude-cost-mcp

by firstshout
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

caching_breakeven

Calculate the break-even point for prompt caching given the static token count and number of reuses. Determines when caching is cost-effective.

Instructions

Compute prompt-caching savings and break-even for a static prompt reused N times. Break-even is ~1.28 reuses.

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": {
      "prompt_tokens": "<prompt_tokens>",
      "reuses": "<reuses>"
    },
    "name": "caching_breakeven"
  }
}

Input Schema

NameRequiredDescriptionDefault
prompt_tokensYesSize of the static (cacheable) prompt in tokens
reusesYesHow many times the prompt is reused
modelNosonnet-4.5

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.8/5.0
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 discloses the break-even threshold (~1.28 reuses) but does not explain the output format, side effects, or model parameter impact.

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 short sentences, no fluff, key information front-loaded (verb and resource first).

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 computation tool without output schema or annotations, the description covers the core purpose and a key insight. It could detail the output but remains adequate.

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 67% (prompt_tokens and reuses have descriptions). The description adds context about static prompts but does not clarify the model parameter or its effect on the calculation.

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 'Compute' and the resource 'prompt-caching savings and break-even for a static prompt reused N times', distinguishing it from sibling tools like batch_savings or estimate_cost.

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 usage for static prompts and caching scenarios but does not explicitly state when to use or avoid this tool, nor does it mention alternatives.

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

Deploy Server

Other Tools