What does Text2sim MCP Server do?
It takes a natural language description of a process, converts it into a SimPy simulation configuration, runs the simulation, and returns performance metrics like average wait times and completed counts.
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基本信息
Text2Sim MCP Server is a discrete-event simulation engine that generates and executes flexible SimPy-based models from natural language descriptions. Supports multi-domain workflows (airport, healthcare, manufacturing) with configurable entities, stochastic logic, and real-time m
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"Text2Sim MCP Server": {
"command": "uv",
"args": [
"--directory",
"PATH_TO_TEXT2SIM_MCP_SERVER",
"run",
"mcp_server.py"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Text2sim MCP Server is a discrete-event simulation engine that generates and executes flexible SimPy-based models from natural language descriptions. It integrates with large language models via the Model Context Protocol (MCP), enabling powerful simulation capabilities within natural language environments like Claude Desktop.
Install Python 3.12 or higher and the uv package manager. Clone the repository, then configure Claude Desktop by adding a block to claude_desktop_config.json that points uv to the mcp_server.py file. After setup, you describe a simulation in plain English (e.g., “Simulate a hospital with triage, diagnosis, and treatment”) and the LLM translates it into a configuration dictionary that the server runs as a SimPy simulation.
uniform, normal, exponential).eval() used.It takes a natural language description of a process, converts it into a SimPy simulation configuration, runs the simulation, and returns performance metrics like average wait times and completed counts.
You need Python 3.12+ and the `uv` package manager. After cloning the repo, add the server configuration to Claude Desktop’s `claude_desktop_config.json` as shown in the README.
The `distribution` field accepts `uniform(min, max)`, `normal(mean, std)` (or `gauss`), and `exp(mean)`. All inputs are parsed safely with regex.
Yes. It uses regex-based parsing for distribution inputs, never `eval()`. Input validation and error handling prevent arbitrary code execution and information leaks.
For each process step, the server returns the average wait time and the number of entities that completed that step – for example, `check_in_wait_time_avg` and `check_in_completed_count`.
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