"A source for everyday AI news and updates" matching MCP servers:

Carbon-aware MCP scheduler that defers "do it later" / "by tomorrow" / "overnight" LLM tasks to the cleanest electricity-grid hour inside a deadline — 40-70% lower CO2 per task, 50% cheaper via Anthropic/OpenAI Batch APIs. 9 MCP tools, per-task carbon receipts to local SQLite, Apache-2.0.

MCP server that provides live facility data access and operational tools, enabling the AI agent to query sensor readings, HVAC status, energy usage, alerts, and execute confirmed maintenance actions.

Exposes EnergyPlus simulation control (run, parse metrics, edit schedules) as LLM tools for autonomous building energy optimization.

Enables users to ask directly within a Claude Code or Codex chat how much energy and CO2eq their current session or entire project has consumed, estimated locally from session logs with no telemetry or network calls. It also reports everyday-activity equivalents such as kettle boils or washing machine cycles for the resulting figures.

Provides LLMs with access to news and information about renewable energy projects and planning in Germany via the Nefino API, enabling location-based queries with topic and date filtering.

A physics engine for liquid-cooled GPU systems, exposed as an AI-callable MCP server. Enables thermal analysis, coolant comparison, flow optimization, and rack-level sizing via natural language queries.

Open-source MCP servers exposing US solar data (production, resource, economics, market, forecast) as agent-accessible tools with a consistent data envelope.

DeepPVMapper is an open source, crowdsourced verified AI map of rooftop solar systems. The MCP serves as a endpoint to allow queries to the database (1.1M+ systems) in natural language. This work is based on my former PhD work.

Enables users to consult and download second copies (2ª via) of Comgás gas bills from the official source via a read-only tool, with prepaid per-query credit.

Read-only MCP server for consulting CPFL utility data via official source using link and OCR, with prepaid per-query pricing.

Read-only MCP server to consult Neoenergia (Elektro) energy bills via official source with OCR, pay-per-query.

Enables calculation of the most economical fuel (gasoline, ethanol, or natural gas) based on prices and vehicle consumption, following the 70% rule for ethanol and 60% for GNV.

Enables utility operators to forecast transformer oil temperature, assess synthetic outage risk, rank impacted assets, and generate maintenance plans through IBM Bob MCP tools.

Nine tools for indoor climate and household energy in Germany/EU: BTU sizing for a room, portable-AC window-seal length, live heatwave outlook, appliance running costs, heating watts, dew point for safe ventilation, and balcony-storage subsidy rules. Also searches and reads 133 guides on getecoback.com; no auth, no personal data, and every answer returns its source URL.

Exposes EnergyPlus building simulation tools as MCP endpoints, enabling LLMs to run closed-loop energy optimization while maintaining occupant comfort.

Hourly electricity grid carbon intensity (gCO2eq/kWh) for 45 zones across Europe, the US and Great Britain, computed from ENTSO-E, EIA and NESO generation data. Four read-only tools; every value carries its interval timestamp and how stale it is. No API key, no account.

An unofficial read-only MCP server for Panasonic AiSEG2 home energy management controllers, enabling clients to read live power flow, per-circuit consumption, circuit names, daily totals, and historical energy/cost data from the device's local web interface.

Unofficial MCP server for the messdienst24.de utility portal, providing tools to retrieve heating and hot-water consumption data, download PDF reports, and compare usage trends.

An MCP server that lets an MCP client control IKEA TRÅDFRI smart plugs paired to a DIRIGERA hub via its local REST API.

Read-only MCP server for Home Assistant that computes statistical summaries, trends, and session detection from recorded sensor history, returning compact tables instead of raw data so small local models can answer questions about energy usage, climate, and appliance activity without token-heavy arithmetic.