PyPSA MCP
PyPSA MCP is a Model Context Protocol (MCP) server for creating, analyzing, and optimizing energy system models using PyPSA (Python for Power System Analysis).
README
PyPSA MCP
PyPSA MCP is a Model Context Protocol (MCP) server for creating, analyzing, and optimizing energy system models using PyPSA (Python for Power System Analysis).
A Model Context Protocol (MCP) server that enables Large Language Models (LLMs) like Claude to interact with PyPSA for energy model creation and analysis via natural language.
Demo Example
Below is a demo video showing how to use PyPSA MCP with Claude. The video demonstrates creating a simple two-bus model, running power flow calculations, and performing optimization.
https://github.com/user-attachments/assets/5633a431-7c3b-4a2f-9a9e-395dcbbb2e29
Demo Prompt
You can try this exact prompt with Claude to reproduce the example shown in the video:
I'd like to build an energy system model and perform optimization using PyPSA. Please help me with these steps:
1. Create a simple two-bus model with:
1. Two buses at (0,0) and (100,0) with 220 kV nominal voltage
2. A generator at bus1 with 100 MW capacity and 50 €/MWh cost
3. A load at bus2 with 80 MW demand
4. 24 hourly snapshots for January 1, 2025
2. Run a power flow calculation to verify the model
3. Perform optimization with the highs solver using the kirchhoff formulation
4. Discuss the results
Overview
PyPSA MCP provides a bridge between Large Language Models and PyPSA, allowing you to:
- Create and manage energy system models through natural language
- Add network components like buses, generators, and transmission lines
- Set up time series data for simulation
- Run power flow and optimization calculations
- Analyze results
Features
-
Model Management
- Create new PyPSA energy models
- List and select from available models
- Export detailed model summaries
- Delete models when no longer needed
-
Component Creation
- Add buses, generators, loads, and other network components
- Configure component parameters through natural language
- Modify existing components
- Organize components into meaningful groups
-
Data and Simulation
- Set time snapshots for simulation periods
- Add time series data for loads and generators
- Run power flow calculations
- Perform optimization with various solvers and formulations
-
Results Analysis
- Extract key metrics from simulation results
- Generate summaries of model performance
- Export data for further analysis
Installation
Prerequisites
- Python 3.10 or higher
- uv (recommended for easy dependency management)
Main Installation (PyPI)
# Install from PyPI
pip install pypsamcp
# Or using uv (recommended)
uv pip install pypsamcp
Running PyPSA MCP
# Run using the installed package
pypsamcp
Configuring in Claude Desktop
-
Locate Claude Desktop's configuration file (typically in
~/.config/Claude/config.json) -
Add PyPSA MCP to the
mcpServerssection:"mcpServers": { "PyPSA MCP":{ "command": "uv", # Sometimes /path/to/local/uv (remove this comment) "args": [ "run", "--with", "pypsamcp", "pypsamcp" ] } } -
Save the configuration file and restart Claude Desktop
Development Installation (from GitHub)
For contributors or users who want to modify the code:
# Clone the repository
git clone https://github.com/cdgaete/pypsa-mcp.git
cd pypsa-mcp
# Install development dependencies with uv
uv pip install -e ".[dev]"
Running in Development Mode
# Run the server directly
python -m pypsamcp.server
Available Tools
The server provides the following MCP tools:
Model Management
create_energy_model(
id: str,
name: str = None,
description: str = None
)
list_models()
delete_model(
id: str
)
export_model_summary(
id: str,
include_components: bool = True,
include_parameters: bool = True
)
Component Creation
add_bus(
model_id: str,
name: str,
v_nom: float,
x: float = 0.0,
y: float = 0.0,
carrier: str = "AC"
)
add_generator(
model_id: str,
name: str,
bus: str,
p_nom: float,
marginal_cost: float = 0.0,
carrier: str = "generator"
)
add_load(
model_id: str,
name: str,
bus: str,
p_set: float
)
add_line(
model_id: str,
name: str,
bus0: str,
bus1: str,
x: float,
r: float = 0.0,
g: float = 0.0,
b: float = 0.0,
s_nom: float = 0.0
)
add_storage(
model_id: str,
name: str,
bus: str,
p_nom: float,
max_hours: float,
efficiency_store: float = 1.0,
efficiency_dispatch: float = 1.0,
standing_loss: float = 0.0
)
Data and Simulation
set_snapshots(
model_id: str,
start_time: str,
end_time: str,
freq: str = "H"
)
run_powerflow(
model_id: str,
snapshot: str = None
)
run_optimization(
model_id: str,
solver_name: str = "glpk",
formulation: str = "kirchhoff"
)
Example Prompts
Here are some examples of how to use PyPSA MCP with Claude:
Create a new energy system model with three buses, two generators, and a load.
Add a wind generator with 100 MW capacity to bus "bus1" with a marginal cost of 10.
Run a power flow calculation on the current model and show me the results.
Optimize the model using the GLPK solver and summarize the key findings.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.