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Text2sim MCP Server

@IamCatoBot

リポジトリ

基本情報

カテゴリ

生産性

ライセンス

MIT license

トランスポート

stdio

作者

IamCatoBot

Text2sim MCP Server について

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

Text2sim MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "Text2Sim MCP Server": {
      "command": "uv",
      "args": [
        "--directory",
        "PATH_TO_TEXT2SIM_MCP_SERVER",
        "run",
        "mcp_server.py"
      ]
    }
  }
}

Text2sim MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Text2sim MCP Server?

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.

How to use Text2sim MCP Server?

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.

Key features of Text2sim MCP Server

  • Create simulation models using plain English descriptions.
  • Supports multiple domains: airport, healthcare, manufacturing, and more.
  • Define custom entity attributes and behaviors.
  • Configure steps with probability distributions (uniform, normal, exponential).
  • Collect real-time metrics like wait times and throughput.
  • Secure regex-based parsing – no eval() used.

Use cases of Text2sim MCP Server

  • Simulate passenger processing at a small airport with check-in, security, and boarding.
  • Model hospital triage, diagnosis, and treatment flows with staffing limits.
  • Analyze manufacturing line throughput and bottleneck detection.
  • Evaluate queuing systems for service counters or call centers.

よくある質問

1

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.

2

How do I install and run the server?

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.

3

What probability distributions are supported?

The `distribution` field accepts `uniform(min, max)`, `normal(mean, std)` (or `gauss`), and `exp(mean)`. All inputs are parsed safely with regex.

4

Is the server secure?

Yes. It uses regex-based parsing for distribution inputs, never `eval()`. Input validation and error handling prevent arbitrary code execution and information leaks.

5

What metrics does a simulation return?

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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