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
MCP server metadata
- Name
- modelruler-inference-calculators
- Version
- 1.0.0
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.
Inferred read-onlyprovider-cost-calculatorUse when a user asks what an LLM workload costs on a specific provider/model, or wants to compare cost across providers.
Inferred read-onlyself-host-breakeven-calculatorUse when a user is deciding between API usage and self-hosted GPU inference at a given volume.
Inferred read-onlycontext-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).
Inferred read-onlyquantization-calculatorUse when a user is planning to quantize an LLM to fit on smaller hardware.
Inferred read-onlyfine-tune-roi-calculatorUse when a user is considering fine-tuning vs prompt engineering.
Inferred read-onlyobservability-cost-calculatorUse when a user needs to budget LLM observability tooling.
Inferred read-onlyrag-pipeline-cost-calculatorUse when a user needs end-to-end RAG cost estimation (embedding + vector store + generation).
Inferred read-onlyautomation-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.
Inferred read-onlyagent-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.
Inferred read-onlyagent-loop-cost-calculatorUse when a user is running multi-step LLM agents and needs cost per successful task.
Inferred read-onlyCONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.modelruler-inference-calculators]
url = "https://modelruler.dev/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"modelruler-inference-calculators": {
"type": "http",
"url": "https://modelruler.dev/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: modelruler-inference-calculators
Remote MCP URL: https://modelruler.dev/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"modelruler-inference-calculators": {
"url": "https://modelruler.dev/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"modelruler-inference-calculators": {
"type": "http",
"url": "https://modelruler.dev/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "modelruler-inference-calculators",
"transport": "streamable-http",
"url": "https://modelruler.dev/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Trust Data Available
BuiltWith Trust API v2 evidence for modelruler.dev was fetched 2026-08-03T13:09:13.461Z and is being refreshed.
modelruler.dev is assessed as Neutral: No suspicious signals found, but no strong positive signal either
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.