AI & Machine Learning
modelruler.dev
Provides utilities for estimating token usage, provider costs, self-hosted GPU breakeven, context window fits, and quantization plans for large language models.
ENDPOINT 1
https://modelruler.dev/mcp
Known tools 12
token-counterUse when a user asks how many tokens a given text will consume, or needs to estimate prompt size before pricing a workload.
provider-cost-calculatorUse when a user asks what an LLM workload costs on a specific provider/model, or wants to compare cost across providers.
self-host-breakeven-calculatorUse when a user is deciding between API usage and self-hosted GPU inference at a given volume.
context-window-plannerUse 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-calculatorUse when a user is planning to quantize an LLM to fit on smaller hardware.
fine-tune-roi-calculatorUse when a user is considering fine-tuning vs prompt engineering.
eval-cost-calculatorUse when a user needs to budget an LLM evaluation run.
observability-cost-calculatorUse when a user needs to budget LLM observability tooling.
rag-pipeline-cost-calculatorUse when a user needs end-to-end RAG cost estimation (embedding + vector store + generation).
automation-cost-calculatorUse when a user needs to compare workflow automation platform cost across Zapier task billing, Make credit billing, and n8n execution billing for a recurring workflow shape.
agent-workflow-cost-calculatorUse when a user needs to estimate automation-platform cost for an agent workflow, including app-action fan-out and MCP tool-call accounting, separate from LLM token spend.
agent-loop-cost-calculatorUse when a user is running multi-step LLM agents and needs cost per successful task.