Model Context Protocol

ProjectEOL MCP Server

Weather and renewable energy forecast tools for AI agents.

ProjectEOL MCP Server gives LLM clients and AI agents access to global weather forecasts, special meteorological metrics, and solar/wind energy generation estimates via the Model Context Protocol.

What AI agents can do

  • Get a weather forecast by coordinates.
  • Analyze temperature, wind speed, precipitation, and other forecast parameters.
  • Calculate special meteorological metrics for analytics and automation.
  • Estimate forecast generation for a solar or wind power plant.
  • Use weather data in automated reports, scenarios, and decision-support workflows.

Who it is for

AI agent developers

Connect live ProjectEOL forecast data to agent workflows and tools.

MCP client users

Use ProjectEOL from Claude Desktop, Cursor, Codex, ChatGPT-compatible workflows, and other MCP clients.

Weather and energy teams

Bring weather-aware and renewable-energy-aware data into analysis and automation.

Available MCP tools

get_weather_forecast

Returns forecast weather data for a specified point: temperature, wind, precipitation, and other parameters.

get_special_weather_metrics

Calculates additional meteorological indicators based on the forecast, useful for analytics and automated scenarios.

get_energy_forecast

Estimates forecast generation for a solar or wind power plant using coordinates and object parameters.

The MCP server wraps only the APIs described on the Base, Special, and Predict solar and wind API pages.

Example requests

Get a weather forecast for coordinates 55.75, 37.62 for the next 24 hours. Estimate whether strong wind is expected tomorrow near this wind power plant. Calculate the forecast generation of a solar power plant for the specified coordinates. Compare weather conditions at two locations.

Connection

ProjectEOL MCP works as a remote HTTPS MCP server. Access uses a ProjectEOL API JWT token.

Endpoint:

https://projecteol.ru/en/mcp/

Authorization:

Authorization: Bearer <PROJECTEOL_JWT_TOKEN>

You can also pass the token in the token parameter when calling a tool. Requests through MCP are counted in the same ProjectEOL user statistics and consume the limits of the corresponding API package.

API access and tokens are managed through the existing ProjectEOL account and API subscription system. If automatic token issuing is not available for your account, request access according to the current ProjectEOL API rules.

Why MCP

MCP connects external data sources to LLM clients and AI agents as standardized tools. With ProjectEOL MCP, an agent can use current forecast data instead of relying only on static model knowledge.

For MCP directories

Recommended listing title:

ProjectEOL Weather & Renewable Energy MCP Server

Short description:

Global weather forecasts and solar/wind generation forecast tools for AI agents.

Keywords:

weather, forecast, renewable energy, solar, wind, NOAA, meteorology, geospatial, energy, MCP, AI agents