Model Ruler — AI Cost Calculators

Connect Remote server

claude mcp add --transport http model-ruler https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry

{
  "mcpServers": {
    "model-ruler": {
      "url": "https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry"
    }
  }
}

{
  "servers": {
    "model-ruler": {
      "type": "http",
      "url": "https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry"
    }
  }
}

Settings > Connectors > Add custom connector
URL: https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry

Tools 12 found in our last check

• 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 measurements.

• 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 comparison table.

• 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.

• rag-pipeline-cost-calculator

  Use when a user needs end-to-end RAG cost estimation (embedding + vector store + generation). Returns monthly cost with breakdown and dominant-component identification.

• automation-cost-calculator

  Use for generic or non-agent recurring workflow platform billing across Zapier task billing, Make credit billing, and n8n execution billing. Use agent-workflow-cost-calculator instead when the workflow is explicitly an AI agent with app actions or MCP tool calls. Use agent-loop-…

• agent-workflow-cost-calculator

  Use for automation-platform/iPaaS cost of an AI agent workflow, including app-action fan-out and MCP tool-call accounting, explicitly excluding LLM token spend. Use automation-cost-calculator for generic non-agent workflow billing. Use agent-loop-cost-calculator for LLM inferenc…

• agent-loop-cost-calculator

  Use for LLM inference/reasoning cost per successful multi-step agent task, including failure overhead and context growth across turns. Use agent-workflow-cost-calculator for iPaaS/app-action/MCP orchestration fees. Use automation-cost-calculator for generic Zapier/Make/n8n workf…

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