"Google Pub/Sub" matching MCP servers:

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.

Enables natural-language querying of US utility emissions, generation mix, and climate alignment data through any MCP client.

Start with execute_plan. Live, dated data for data center, colocation, power grid, site selection, interconnection and energy questions. Rank data center and datacenter markets, check interconnection queues and grid headroom across PJM, ERCOT, CAISO, MISO, SPP, NYISO and ISO-NE, pull electricity and natural gas prices, and review fiber. Cited answers. Connect: https://dchub.cloud/mcp

Enables AI agents to answer data-center siting questions by querying a live facility registry, per-metro market intelligence, real-time grid fuel mix and demand, and leasable capacity listings, including a one-call planner that combines these into ranked, cited answers. Results are fetched live per request, keyless, with optional API keys for fuller responses.

DC 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.

MCP server that enables Google ADK agents to triage solar fault signals, retrieve Salesforce diagnostics via hosted MCP prompt templates, and create WorkOrder records when replacements are needed.

Generates peer comparison reports on emissions trends, reduction targets, and gaps for companies in a given SICS sector/sub-sector using live data from the Climate Data Utility (CDU).

An MCP server that provides access to Northwood Capital Partners' portfolio carbon data, enabling MCP-compatible agents to query emissions, analyze decarbonization gaps, and simulate reduction initiatives through natural language.

MCP server enabling AI assistants to automatically perform carbon footprint modeling, product queries, and emission analysis via the Carbonstop Cloud API.

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 AI assistants to automatically call Carbonstop Cloud API for carbon footprint modeling, product query, and emission analysis through natural language.

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.

Enables rooftop solar installers to turn a CSV of tomorrow's booked jobs into a ranked crew schedule in Markdown and JSON, joining per-address geocoding, roof pitch/azimuth from the Google Solar API, hourly forecast checks against crew-safety thresholds, and estimated plane-of-array irradiance. Each job is returned as KEEP, MOVE (with a new same-day start) or SLIP, together with the specific rule that decided it.

Turns Google Solar API roof data for a single building into an installer-ready geometry packet with per-segment pitch, azimuth, area, sunshine and derived usable area, steepness, complexity and shading, plus JSON, Markdown and an SVG sketch. Optionally adds pre-GA roof geometry data with facet polygons and obstacles.

Enables voice assistants to answer when to run household appliances using live solar forecasts, typical-year production, savings, battery, and multi-load planning. It remembers site details, estimates usable solar windows, and returns concise spoken guidance without inventing measurements.