REE MCP Server
Related Servers
Alternatives to REE MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to access and analyze Spanish electricity consumption data via the Datadis API, providing tools for supply management, consumption analysis, anomaly detection, and executive reporting.MIT
- AlicenseNot gradedqualityDmaintenanceA Model Context Protocol server that provides real-time access to Spanish electricity demand, weather data, and generation mix, enabling AI agents to analyze and summarize energy information.MIT
- AlicenseNot gradedqualityAmaintenanceDC Hub is the live data layer for data-center siting that agents can query and cite. Its Data Center Power Index (DCPI) scores where data centers can get grid power across 300+ markets daily. Also 330,000+ mapped power, grid, gas and fiber assets. 94 MCP tools at https://dchub.cloud/mcp plus a REST API at https://dchub.cloud/api/v1. Free tier needs no key; paid plans: dchub.cloud/pricing.MIT
- AlicenseAqualityDmaintenanceEnables real-time solar data from Fronius inverters via Claude, allowing natural language queries about solar production, battery, and grid exchange.51Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables real-time access to US electricity generation, fuel mix, and demand data through natural language queries.31 npmMIT
- FlicenseNot gradedqualityDmaintenanceEnables AI-powered analysis and prediction of household energy consumption through machine learning models, providing historical consumption breakdowns, price queries from Spanish electricity markets, and personalized energy optimization recommendations.-
TDQS
Scored across 18 tools
Most tools have clearly distinct purposes (demand, generation, prices, etc.), but get_indicator_data is a generic tool that can retrieve many of the same data types as dedicated tools, potentially causing confusion about which to use.
All tool names follow a consistent verb_noun snake_case pattern (e.g., get_carbon_intensity, list_indicators), making the set predictable and easy to navigate.
With 18 tools covering various aspects of electricity grid data (demand, generation, prices, storage, etc.), the count is well-scoped and each tool serves a specific role.
The tool surface covers major domain operations: demand, generation mix, carbon intensity, prices, storage, international exchanges, and indicator discovery. The generic get_indicator_data fills any gaps.