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    MCP server for fetching Danish electricity spot prices (DK1/DK2) using the free elprisenligenu.dk API, providing tools to get current price, cheapest hours, and price summaries.
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    MIT
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    Enables Claude to size batteries, wire gauges, and fuses for 12V-48V electrical systems in boats, vans, and off-grid builds, and generates complete wiring diagrams as SVG or PNG.
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    MIT
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    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.
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    MCP server for real-time electricity prices, carbon intensity, and energy analytics across 41+ zones in Europe, Great Britain, the United States, and Australia. Query live prices, compare zones, check gas storage levels, get green scores, find optimal charging windows, and access advanced analytics. Free Basic tier requires no API key. Install via npx gridpulse-mcp or connect directly via Streamab
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    A Model Context Protocol server that connects Claude to your own Kia vehicle through the Kia Owners API, enabling vehicle status, location, odometer, EV charge state, and confirm-gated commands for doors, climate, and charging.
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    MIT
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    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.
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    MIT
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    Enables discovery and control of Philips Hue lighting devices via a local bridge using the CLIP v2 API, without any cloud dependency.
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    MIT
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    The PGIQ Rating as agent tools: where to site or schedule a large electricity load across 67 global power markets. Wraps a read-only REST API returning reasoned, cited ratings across access, availability, cost, momentum, and carbon, plus live grid snapshots and cheapest-window scheduling.
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    MIT
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    Connect AI assistants to Victron Energy systems to read real-time solar, battery, grid, and inverter data from your local network via Modbus TCP or MQTT.
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    MIT
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    A lean Model Context Protocol (MCP) server that gives AI assistants like Claude structured access to a SolarEdge PV installation via the official SolarEdge Monitoring API.
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    MIT
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    Enables LLM agents to query live data from Anker Solix solar systems (Solarbank, expansion batteries, Smartmeter) via natural language, such as current solar production or battery state of charge.
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    MIT
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    Description: Data-center, power & gas intelligence MCP server. 33 tools covering 21,000+ data-center facilities (170+ countries), 232 US power markets scored by the DC Hub Power Index (DCPI), 2,000+ tracked M\&A deals, ISO grid telemetry (PJM, ERCOT, CAISO, MISO, SPP, NYISO), fiber routes, energy pricing. License: Free to cite (CC-BY-4.0). Existing distribution: In the official MCP registry; indexe
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    MIT
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    An unofficial MCP (Model Context Protocol) server that exposes a Vaillant heat pump's data to AI assistants like Claude. Query outdoor and room temperatures, hot water status, energy consumption, COP estimates, schedules, and diagnostics through natural conversation.
    4
    MIT
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    A Model Context Protocol server providing free financial market data across 13 categories with 83 no-key tools, enabling access to stocks, indices, options, forex, crypto, energy, prediction markets, and more.
    83
    MIT
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    Enables AI assistants to query Tesla vehicle data and analytics from a TeslaMate PostgreSQL database, including battery health, driving statistics, charging sessions, and custom SQL queries.
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    MIT
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    Fits a lithium-ion full-cell dual-water-tank model from charge/discharge voltage-capacity data for battery aging mechanism identification, with parameter fitting, batch processing, and MCP server integration.
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    Apache 2.0
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    Enables querying optimal control values (angle for blowers, control for pumps) to minimize power given a required flow rate, using machine learning models trained on pump/fan operation data.
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