Grid Operations MCP Suite

This project implements a Model Context Protocol (MCP) suite for power grid operations research, enabling Large Language Models (LLMs) to interact with real-time grid data, analytics tools, and visualization resources.

Features

• MCP Server: Provides grid operations tools for load analysis, outage prediction, and visualization.
• MCP Client: Connects to the server, manages queries, and handles tool execution.
• Host Integration: Formats prompts and tool descriptions for LLMs.
• Model Flexibility: Supports multiple LLM providers via AI Suite integration.
• Best Practices: Includes guidelines for security, performance, and error handling.

Getting Started

Prerequisites

• Python 3.8 or higher
• Required packages:
  • mcp
  • aisuite
  • pandas
  • matplotlib
  • numpy
  • aioconsole
  • python-dotenv
• Set up environment variables (e.g., API keys) in a .env file.

Running the Server

python grid_ops_server.py

Running the Client

python grid_ops_client.py grid_ops_server.py [initial_model]

• Replace [initial_model] with your chosen LLM model (e.g., openai:gpt-4o).

Usage

• Enter operational queries at the prompt.
• Switch LLM models dynamically using model:provider:model_name.
• Type context to view the current operational context.
• Type quit to exit the client.

Example Query

Analyze load patterns in the Northeast region for the last 48 hours.

Best Practices

• Use descriptive tool names and detailed JSON schemas for clarity.
• Validate all tool inputs and handle errors gracefully.
• Enable authentication and HTTPS for production environments.
• Monitor performance and optimize tool implementations as needed.

Troubleshooting

• Refer to mcp_troubleshooting.md for solutions to common issues.

Project Structure

• insecure_demos/mcp/
  • attack-mcp-client.py: Demonstrates a vulnerable MCP client implementation (for demo purposes only).
  • vuln-mcp.py: Contains vulnerable MCP code examples (for demo purposes only).
• ai_suite_integration.py: Manages integration with LLM providers.
• grid_ops_client.py: Client for interacting with the MCP server.
• grid_ops_host.py: Handles LLM host integration.
• grid_ops_research_example.py: Example script for grid operations research.
• grid_ops_server.py: Implements the MCP server with grid tools and resources.
• mcp_best_practices.py: Contains best practices and configuration details.
• mcp_theory.py: Theoretical background and concepts for MCP.
• mcp_troubleshooting.md: Troubleshooting guide for common issues.
• README.md: Project documentation (this file).

License

This project is licensed under the MIT License.

Acknowledgments

• Inspired by Andrew Ng's AI Suite and the Model Context Protocol (MCP) community.