"Information related to Python programming or the Python language" matching MCP servers:

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.

An MCP server that exposes the U.S. Energy Information Administration (EIA) Open Data API, enabling LLMs to browse and query energy data across 17 datasets with generic, composable tools.

Enables Claude or any MCP client to read live and historical Sunsynk inverter, battery, and solar data, plus inverter settings, through the Sunsynk Connect cloud API. It is read-only and lets users ask natural-language questions about generation, consumption, charging, and configuration.

MCP server for converting OEM energy telemetry payloads into ODS-E records and validating them via the odse Python package.

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.

Enables AI assistants to compile distribution feeders, run power flow, voltage and thermal violation checks, short-circuit and Thévenin impedance studies, hosting capacity and QSTS analyses, and add or edit elements, through 20 typed tools that return structured JSON or Markdown with the inputs that produced the results.

Enables users to query and download Cemig electricity bills from official sources via natural language, with read-only access and pre-paid credits across various MCP clients.

Browse and query the U.S. Energy Information Administration API v2 — electricity, petroleum, natural gas, coal, forecasts, and more via MCP. STDIO or Streamable HTTP.

Enables access to US Energy Information Administration statistics including production, consumption, prices, exports, and more, with series search and natural-language queries.

An MCP server that wraps the U.S. Energy Information Administration's Open Data API, enabling assistants to fetch live energy data via natural language. It provides tools for querying series, browsing data routes, filtering facets, and running custom queries.

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

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

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 Model Context Protocol (MCP) server that provides comprehensive access to Tigo Energy solar system data and analytics. It enables AI assistants to interact with your Tigo solar monitoring system to retrieve production data, performance metrics, system health information, and maintenance insights.

Enables searching and retrieving US electricity tariff data from NREL's OpenEI Utility Rate Database, including rate schedules, charges, and utility information for locations.

MCP server for the Carbon Interface API (v1), enabling AI agents to estimate carbon emissions through natural language queries via Pipeworx gateway.

Enables querying the official ANP Base de Distribuição database for distribution base information through a read-only, hosted MCP endpoint with prepaid per-query credits.

Provides access to KfW funding programs for residential building energy efficiency renovations in Germany. Enables users to list programs, check eligibility, calculate funding amounts, and get detailed information about specific KfW loans and grants.

Exposes Frank Energie energy data (electricity and gas prices, account info) as MCP tools for LLMs, using python-frank-energie for API communication.

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.