"A framework for building cross-platform mobile applications using Flutter" matching MCP servers:

Enables users to compare air, rail, maritime, and electric ground freight options using GLEC emissions factors, optimize multi-carrier routes, and compute carbon footprints with offset costs. It also generates verified carbon offset credit allocation certificates.

Autonomous, carbon-aware building management system that pairs EnergyPlus digital twins with LLMs via the Model Context Protocol (MCP) for dynamic HVAC optimization and grid carbon reduction.

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

Enables users to compare and select multi-carrier freight routes by applying GLEC emissions factors across air, rail, maritime, and electric ground modes while weighing transit time and landed cost. It also calculates the resulting CO2 footprint and generates verified carbon offset credit allocation certificates for the chosen route.

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

MCP server for BIM-to-building-energy simulation workflows with IFC extraction, TEASER integration, scenario modeling, weather binding, and results export for downstream WAT/ROI analysis.

A read-only BACnet/IP gateway that exposes building automation point databases to LLM agents via MCP, with Brick + Project Haystack semantic tagging at ingest time.

MCP server that enables LLMs to interact with Monta's EV charging platform for managing charge points, charging sessions, and wallet operations.

Provides AI agents with read access to Trane Tracer SC+ building automation systems for inventory and telemetry retrieval.

Enables LLM applications to query and visualize data from Bosch/Buderus heat pumps via ems-ESP, including temperatures, statistics, and heat curves through natural language.

Enables turning an address or lat/lng into a transparent solar proposal by geocoding it, pulling Google Solar API building insights (panel layouts, roof segments, imagery quality), and pricing a few system sizes with your tariff, install cost, incentives, savings, payback, NPV and a verdict. Every input is labelled with its source, Google's own financial analyses are shown side by side, and no prices are invented.

Enables querying NASA POWER historical solar, wind, building, and agroclimatology data via MCP, including point time series, climatologies, native-grid regions, and comparisons across multiple labeled locations, with staged SQL analysis for larger datasets. Runs over STDIO or Streamable HTTP and requires no NASA account or API key.

A local MCP server that enables building energy analysis through tools for anomaly detection, flexible-load schedule optimization, and battery/solar outage-autonomy simulation using reproducible synthetic data.

This MCP server provides a single read-only tool to query official CPFL (electric utility) bill download data via a hosted, prepaid service without requiring platform credentials.

PyPSA MCP is a Model Context Protocol (MCP) server for creating, analyzing, and optimizing energy system models using PyPSA (Python for Power System Analysis).

Read-only MCP server for querying Enel Rio de Janeiro's official list of installations using a single tool, hosted with prepaid pay-per-use pricing.

Enables prospecting lists of addresses, points or a bounding box through the Google Solar API's detected-arrays insight, reporting for each building whether rooftop PV is already detected, how old the capture imagery is, and how strong the roof's solar potential is. It ranks the remaining buildings into a reviewable prospect list while tracking call budget and list-price cost.

MCP server for querying ENTSO-E Transparency Platform data including actual load, generation per type, cross-border flows, and installed capacity.

Enables AI agents to understand, query, and manipulate Honeybee building energy models through natural language via the Model Context Protocol.

Enables AI agents to interact with the OSDU® data platform through Model Context Protocol, providing tools for search, storage, schema management, and dataset operations.