PyPSA MCP: Energy Modeling for LLMs
About
PyPSA MCP enables natural language interaction with energy system models through a Model Context Protocol server.
Details
- Author
- cdgaete
- Downloads
- 210
- Categories
- Other
Jump to
- Create energy system models using natural language
- Manage components: buses, generators, loads, transmission lines
- Set up time series data for renewable generation and demand
- Run power flow and optimization calculations
- Built on PyPSA (Python for Power System Analysis)
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
PyPSA MCP: Energy Modeling for LLMsCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Users interact with the server via natural language prompts to describe energy system components and desired analyses. The server translates these prompts into PyPSA operations, enabling model creation, modification, and simulation without writing code directly.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"pypsa mcp: energy modeling for llms": {
"PyPSA MCP": {
"command": "uv",
"args": [
"run",
"--with",
"pypsamcp",
"pypsamcp"
]
}
}
}
}McpServers
{
"PyPSA MCP": {
"command": "uv",
"args": [
"run",
"--with",
"pypsamcp",
"pypsamcp"
]
}
}PyPSA MCP allows users to create, analyze, and optimize energy system models using natural language. Built on PyPSA (Python for Power System Analysis), it provides tools for managing components like buses, generators, loads, transmission lines, setting up time series data, and running power flow and optimization calculations.
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