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openclaw-cost-tracker-mcp

openclaw-cost-tracker-mcp

by temurkhan13
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

model_routing_recommendations

Finds opportunities to replace expensive models like Claude Sonnet 4 with cheaper Gemini 2.5 Flash for extraction or GPT-4o with GPT-4o-mini for short chats, providing 30-day cost savings.

Instructions

Suggestions to route some volume to cheaper providers/models — e.g., claude-sonnet-4 → gemini-2.5-flash for extraction-style work, gpt-4o → gpt-4o-mini for short chats. Each rec includes 30d estimated savings.

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": "model_routing_recommendations"
  }
}

Input Schema

NameRequiredDescriptionDefault
window_hoursNoWindow over which to find candidates (default 720 = 30 days)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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 lacks details on side effects (e.g., does it modify anything?), permissions, limitations, or how suggestions are generated. The description only states output (suggestions with savings) but not behavior beyond that.

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?

The description is two sentences, front-loaded with the main purpose, and uses concrete examples to clarify. Every sentence adds value without redundancy.

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?

The description is adequate for a recommendation tool but lacks details on output format, number of suggestions, or prerequisites (e.g., required cost data). Without output schema, more behavioral context would be helpful for an agent to use it correctly.

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?

The single parameter 'window_hours' is fully described in the schema (coverage 100%). The description adds no additional meaning beyond what the schema provides, so baseline score of 3 applies.

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 provides suggestions to route volume to cheaper providers/models, with specific examples and mention of 30d estimated savings. It is easily distinguishable from sibling tools which focus on cost analysis rather than recommendations.

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 does not explicitly state when to use this tool versus alternatives. While the sibling tool names give implicit context, there is no guidance on when to recommend routing vs. other cost actions, or exclusions for certain scenarios.

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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