AI Footprint
Water and energy footprint of AI use: chat prompts, agent sessions, methodology and sources.
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Calidad y seguridad
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"ai-footprint": {
"url": "https://prompt-tightener-production.up.railway.app/mcp"
}
}
}Puntos de conexión remotos
https://prompt-tightener-production.up.railway.app/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (4)
🟢estimate_ai_footprint(queries_per_day, usage, boundary, days)
Estimate the water (mL) and energy (Wh) used by chat-style AI prompts (ChatGPT, Claude, Gemini etc.). queries_per_day: prompts per day. usage: 'simple' (text chat, ~0.34 Wh/prompt), 'mixed' (~1 Wh), 'intensive' (image generation / deep reasoning, ~3 Wh). boundary: 'onsite' (data-centre cooling only, as vendors report) or 'comprehensive' (adds water used to generate the electricity – the wider boundary most researchers use). days: number of days to total over (e.g. 250 workdays, 365). Returns per-prompt, per-day and total figures with everyday equivalents, assumptions and a source link. For agentic/coding sessions use estimate_session_footprint instead.
Esquema de entrada
{
"type": "object",
"properties": {
"queries_per_day": {
"title": "Queries Per Day",
"type": "number"
},
"usage": {
"default": "simple",
"enum": [
"simple",
"mixed",
"intensive"
],
"title": "Usage",
"type": "string"
},
"boundary": {
"default": "comprehensive",
"enum": [
"onsite",
"comprehensive"
],
"title": "Boundary",
"type": "string"
},
"days": {
"default": 1,
"title": "Days",
"type": "integer"
}
},
"required": [
"queries_per_day"
],
"title": "estimate_ai_footprintArguments"
}🟢get_methodology
Return the per-prompt energy and water figures, accounting boundaries, sources, limitations, a citation line, and why published AI water estimates differ by ~100x (0.3 mL to 50 mL per prompt). Call this before explaining or citing any AI water figure.
Esquema de entrada
{
"type": "object",
"properties": {},
"title": "get_methodologyArguments"
}🟢compare_water_use(water_ml)
Convert a volume of water (mL) into everyday comparisons: teaspoons, 500 mL bottles, shower time, and lifecycle items (A4 sheet, almond, cup of tea, beef burger), plus the number of typical AI text prompts it equals. Includes the boundary caveat that lifecycle footprints are not like-for-like.
Esquema de entrada
{
"type": "object",
"properties": {
"water_ml": {
"title": "Water Ml",
"type": "number"
}
},
"required": [
"water_ml"
],
"title": "compare_water_useArguments"
}🟢estimate_session_footprint(input_tokens, output_tokens, cached_input_tokens, model_class, boundary)
Estimate the water and energy of an AI session (e.g. an agent or coding-assistant run) from its token usage. Pass the SUM across all model calls: input_tokens (uncached prompt tokens), output_tokens (including any reasoning/thinking tokens) and cached_input_tokens (prompt-cache reads). model_class: 'small' (Haiku/mini/Flash-class), 'frontier' or 'reasoning'. Returns a central estimate and a 0.3x–3x range – this is an order-of-magnitude estimate calibrated to published per-prompt figures, not a measurement.
Esquema de entrada
{
"type": "object",
"properties": {
"input_tokens": {
"title": "Input Tokens",
"type": "integer"
},
"output_tokens": {
"title": "Output Tokens",
"type": "integer"
},
"cached_input_tokens": {
"default": 0,
"title": "Cached Input Tokens",
"type": "integer"
},
"model_class": {
"default": "frontier",
"enum": [
"small",
"frontier",
"reasoning"
],
"title": "Model Class",
"type": "string"
},
"boundary": {
"default": "comprehensive",
"enum": [
"onsite",
"comprehensive"
],
"title": "Boundary",
"type": "string"
}
},
"required": [
"input_tokens",
"output_tokens"
],
"title": "estimate_session_footprintArguments"
}Comunidad
Evidencia