"Victron Energy" matching MCP servers:

Provides access to comprehensive U.S. and international energy data from the EIA API, including electricity, natural gas, petroleum, coal, renewables, CO2 emissions, and energy forecasts.

An MCP server that scores the credit health of public energy companies using public data, providing a 0-100 score and factor breakdown. Enables agents to assess financial soundness of utilities, generators, and energy marketers.

Enables AI assistants to clean PDB structures and run initial-stage energy relaxation for biomolecular modeling. It provides a structured workflow for preparing structures before production molecular dynamics or coarse-graining pipelines.

An MCP server that integrates InspireHEP high-energy physics literature with LLMs. Search papers, explore citations, retrieve author metrics, and generate formatted references.

An MCP server that connects LLMs to CERN GitLab to discover and analyze High Energy Physics code, documentation, and analysis examples. It provides 14 tools for repository browsing, dependency parsing, and CI/CD configuration analysis.

Real-time supply chain risk intelligence with 25 tools: Global Disruption Index, Manufacturing Index, commodity prices, port congestion, border delays, chokepoints, air cargo, trade policy, energy, rail, freight, economic indicators, predictive signals, and AI intelligence briefs.

Real-time and historical oil, gas, and commodity prices. 40+ energy commodities including Brent Crude, WTI, Natural Gas, LBMA Gold/Silver, EU Carbon, and refined products. Get current prices, compare commodities, view market overviews, and access historical data — all through natural language. Used by energy traders, fintech companies, and researchers worldwide.

Offline SQLite-backed nuclear physics data server for AI agents, providing atomic masses, nuclear properties, charge radii, energy levels, and more from multiple evaluated databases.

Provides comprehensive access to EnergyPlus building energy simulation results, enabling discovery, analysis, and extraction of data from epJSON, SQL, and HTML files through MCP tools with pandas integration.

A Python-based MCP server that enables searching for high-energy physics literature on INSPIRE-HEP by title, author, or full text. It provides optimized search results including citations, abstracts, and arXiv links while allowing filters for publication date and collaboration size.

Provides 42+ specialized tools for nutrition analysis integrating Canada's Food Guide recipes with Health Canada's official databases (CNF, DRI, EER) for recipe discovery, macro calculations, energy requirements, and dietary adequacy assessments.

Enables AI clients to query public US Department of Energy and national-laboratory data — research literature, datasets, software, patents, EIA grid and BPA operations, facilities, Daymet weather, climate models, sensors, and materials structures — through focused stdio servers. Every answer carries a provenance envelope naming the systems read, when they were read, and what the search did not cover.

Enables searching and retrieving high-energy physics literature, authors, institutions, and conferences from INSPIRE-HEP.

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

Weather files (EPW/DDY) for building energy simulation, on-demand. Four tools: search the 17,000-station catalog, analyze any EPW (design conditions, HDD/CDD, DesignDay IDF emit), render 5 chart types (diurnal, wind rose, temp carpet, monthly box plot, comparison), and generate TMY/AMY/CMIP6-morphed scenarios with UHI, extreme events, and wildfire smoke overlays. 3 of 4 tools work without API key.

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

A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.

Provides tools to list curated climate and energy feeds, read feed items, and fetch any RSS/Atom feed with robust fallback handling.

Enables AI agents to search and retrieve cited evidence packs for renewable energy assets, analyze locations, and access regional energy context, all from a local DuckDB snapshot of Aragon renewable infrastructure data.

Enables 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.