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token-optimization-mcp

token-optimization-mcp

by DCx7C5
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

savings_report

Reduce LLM costs by viewing token savings, cache hits, and estimated USD savings per client for the current session.

Instructions

Token savings dashboard for the current session. Shows cache hits, tokens saved, and estimated USD savings per client.

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": "savings_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNogpt-4o

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It states 'for the current session' implying read-only behavior, but does not explicitly confirm non-destructive nature or any side effects.

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 clear sentences with no unnecessary words. Front-loaded with the primary purpose.

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

Completeness3/5

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

Covers key output contents, but lacks explanation of 'current session' and the optional model parameter. Output schema exists, which somewhat compensates, but incomplete for a full understanding.

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 only parameter 'model' is not mentioned in the description, leaving its purpose and effect unclear. The description should explain how the model parameter influences the report.

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 it is a 'token savings dashboard' showing cache hits, tokens saved, and USD savings, which is distinct from sibling tools like cache_lookup or estimate_tokens.

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 guidance on when to use this tool versus alternatives like cache_lookup or estimate_tokens. No explicit when-not or context for usage.

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

Deploy Server

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