Text2sim MCP Server

🚀 Discrete Event Simulation Module: Text2Sim MCP Server Component

This module adds Discrete Event Simulation (DES) functionality to the Text2Sim MCP server, built using SimPy.

🚀 Quick Start

This module enhances the Text2Sim MCP server by integrating discrete event simulation capabilities, leveraging the power of SimPy.

✨ Features

• Entity Representation: Entities can have custom attributes and track their own states throughout the process.
• Process Step Logic: Encapsulates the logic of individual process steps, including resource management, processing time determination, and performance metric collection.
• Performance Metrics: Collects and aggregates performance metrics during the simulation, such as waiting times and throughput counts.
• Full Simulation Integration: Integrates all components into a complete discrete event simulation, including environment configuration, entity generation, and sequential processing.

📦 Installation

No installation steps provided in the original document.

💻 Usage Examples

No code examples provided in the original document.

📚 Documentation

Structure

• des_simulator.py: Contains the core SimPy-based simulation model, entities, and metric collection code.
• des_utils.py: Utility functions for distribution parsing, configuration validation, and simulation execution.

Module Components

Entity Classes

Represent units flowing through the simulation system. Entities can have custom attributes and track their own states throughout the process.

Process Step Classes

Encapsulate the logic of a single process step. Key features include:

• Resource management with capacity limits.
• Processing time determined by probability distributions.
• Collection of waiting time and throughput metrics.

Metric Collectors

Collect and aggregate performance metrics during the simulation run:

• Waiting time for each process step.
• Throughput counts.
• Automatic calculation of averages and counts.

Simulation Model

Integrates all components into a complete discrete event simulation:

• SimPy environment configuration.
• Entity generation with configurable inter-arrival times.
• Sequential processing of multiple steps.
• Metric collection and reporting.

Supported Distributions

Use in the distribution field of any step:

Configuration Scheme

The simulation engine parses the input configuration using regular expressions, executes the SimPy-based simulation, and returns performance metrics for interpretation.

Security Considerations

• No eval() Usage: Regex-based parsing prevents arbitrary code execution.
• Input Validation: Validates distribution types and parameters before execution.
• Robust Error Handling: Reports errors cleanly without revealing internal states.

🔧 Technical Details

The module uses SimPy to build a discrete event simulation system. It includes entity classes, process step classes, metric collectors, and a simulation model. The simulation engine parses input configurations using regular expressions and validates inputs to ensure security and reliability.

📄 License

No license information provided in the original document.