MCP server

Model Ruler — AI Cost Calculators

io.github.helphub369/model-ruler

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Read-only AI/LLM cost tools with current MCP discovery and attributable Registry transport.

Website

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

12

Token cost

About 3,582 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.model-ruler]
url = "https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry"

Gemini CLI

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

Cursor

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

VS Code

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

Antigravity

agy mcp add model-ruler https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"model-ruler","server_url":"https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"model-ruler","server_url":"https://modelruler.dev/mcp?dist=model_everywhere_registry_native_official_registry"}

Tools

• agent-loop-cost-calculator ~399 tokens
  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 workflow billing.
• agent-workflow-cost-calculator ~279 tokens
  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 inference/reasoning cost per
• automation-cost-calculator ~268 tokens
  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-cost-calculator inste
• context-window-planner ~263 tokens
  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).
• eval-cost-calculator ~349 tokens
  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.
• fine-tune-roi-calculator ~301 tokens
  Use when a user is considering fine-tuning vs prompt engineering. Returns training cost, monthly inference savings, months-to-ROI, and breakeven volume.
• observability-cost-calculator ~224 tokens
  Use when a user needs to budget LLM observability tooling. Returns monthly cost at given request volume with retention adjustment.
• provider-cost-calculator ~270 tokens
  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.
• quantization-calculator ~282 tokens
  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.
• rag-pipeline-cost-calculator ~455 tokens
  Use when a user needs end-to-end RAG cost estimation (embedding + vector store + generation). Returns monthly cost with breakdown and dominant-component identification.
• self-host-breakeven-calculator ~271 tokens
  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.
• token-counter ~221 tokens
  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.

Browse

• GitHub tools
• Zapier tools
• Workflow automation
• Invoicing and accounting
• GitHub and code hosting
• Errors and monitoring

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