LLM Cost Monitor
Tracks LLM API spending across providers including OpenAI, Anthropic, and Gemini. Delivers cost calculators, model comparisons, and budget projections directly in AI development workflows. AI engineers and developers use it to monitor expenses and optimize provider selection.
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|Overview
LLM Cost Monitor is an MCP server that logs and analyzes API usage costs for large language models from multiple providers like OpenAI, Anthropic, and Gemini. It integrates cost tracking into AI pipelines, enabling data-driven decisions on model selection and budgeting.
Key Capabilities
- Cost Tracking: Records API calls and accumulates spend data across supported providers.
- Cost Calculators: Computes projected expenses based on token usage, model pricing, and volume.
- Model Comparisons: Evaluates cost-per-token and performance metrics between models like GPT-4, Claude, and Gemini variants.
- Budget Projections: Forecasts future spend using historical data and usage patterns.
Use Cases
- An AI developer queries costs after running batch inferences on OpenAI GPT-4 and switches to Anthropic Claude when projections exceed budget.
- A team compares token rates for Gemini 1.5 Pro versus OpenAI models during prototype evaluation to select the lowest-cost option.
- Engineering leads generate monthly spend reports from aggregated data to inform vendor negotiations.
- During scaling, project future costs for high-volume deployments across providers to avoid overruns.
Who This Is For
AI developers building applications with multiple LLM providers, engineering teams managing cloud AI expenses, and data scientists optimizing inference costs in production workflows.
PlaygroundUpdated Apr 9, 2026