Model Ruler — AI Cost Calculators

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as io.github.helphub369/model-ruler and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 6 Oct 2026. Not supplied by the maker.

• token-counter

  Use when a user asks how many tokens a given text will consume, or needs to estimate prompt size before pricing a workload. Given text and tokenizer family, returns low/high token range and byte-level

• provider-cost-calculator

  Use when a user asks what an LLM workload costs on a specific provider/model, or wants to compare cost across providers. Given tokens per call and call volume, returns monthly cost plus a tier compari

• self-host-breakeven-calculator

  Use when a user is deciding between API usage and self-hosted GPU inference at a given volume. Returns breakeven token volume, monthly cost comparison, and go/no-go recommendation.

• context-window-planner

  Use when a user needs to know whether a document plus prompt plus output fits within a model's context window, or wants a strategy recommendation (truncate/summarize/rag/chunk).

• quantization-calculator

  Use when a user is planning to quantize an LLM to fit on smaller hardware. Given parameter count and precision transition, returns VRAM requirement, speedup estimate, and approximate quality delta.

• fine-tune-roi-calculator

  Use when a user is considering fine-tuning vs prompt engineering. Returns training cost, monthly inference savings, months-to-ROI, and breakeven volume.

• eval-cost-calculator

  Use when a user needs to budget an LLM evaluation run. Given samples/models/trials, returns total cost, per-run cost, and parallel time estimate.

• observability-cost-calculator

  Use when a user needs to budget LLM observability tooling. Returns monthly cost at given request volume with retention adjustment.

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