ai-usage-cost-analyzer-mcp
Fetches usage metrics from AI providers and computes costs based on token consumption, API calls, and billing rates. Outputs reports on expenses and trends across models and time periods. AI developers, ML engineers, and FinOps teams use it to track spending in LLM deployments.
Overview
The ai-usage-cost-analyzer-mcp MCP server retrieves usage data from AI service providers and performs cost calculations. It processes metrics like input/output tokens and request counts against provider rate cards to deliver expense breakdowns and forecasts.
Key Capabilities
- Retrieve usage statistics from AI APIs such as OpenAI and Anthropic
- Calculate precise costs using current pricing for models and features
- Generate breakdowns, trends, and projections in structured formats like JSON
- Compare costs across providers and models for optimization insights
Use Cases
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Integrate into a dashboard to fetch daily usage and compute costs for GPT models, alerting on budget overruns.
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Analyze historical token data to identify expensive inference patterns in production pipelines.
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Run monthly reports comparing Anthropic Claude vs. OpenAI GPT expenses for procurement decisions.
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Forecast future spend based on usage growth trends for capacity planning.
Who This Is For
- Developers integrating LLMs who need real-time cost visibility
- ML operations engineers tuning deployments for efficiency
- FinOps and finance teams auditing AI cloud expenditures
- Startups and enterprises scaling AI while enforcing budgets