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Measure AI energy, water, CO₂ impact, and prompt efficiency from token usage.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AI Impact MCP" yet — see the docs or source repo.
Using this week's AI token usage data, estimate total energy consumption, cooling water usage, equivalent driving miles, and CO₂ emissions, then provide an overall prompt-efficiency score.
A report summarizing environmental impact metrics and a prompt-efficiency score.
Compare token usage across three prompt sets for the same task, estimate their energy, water, carbon impact, and efficiency scores, and identify the most sustainable option.
A comparison table showing environmental cost by prompt and a recommended option.
Aggregate this month's team AI token usage and produce a sustainability summary including total energy, total CO₂, total water, equivalent driving miles, and actionable prompt optimization recommendations.
A monthly AI environmental impact summary suitable for team review or reporting.
Track AI usage, costs, logs, and debug model interactions across apps.
Estimate GPU needs, training costs, inference spend, and AI infrastructure TCO.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.
Measure CPU energy and LLM token usage to guide efficient refactoring.
Count tokens, estimate costs, optimize prompts, and compare LLM pricing.
Evaluate AI agent outputs for CI gates, regressions, and canary promotions.