# simulation_by_simpy_mcp

> Use this tool when you need to simulate and analyze queueing systems, such as M/M/1, M/M/c, and manufacturing systems, to forecast performance metrics like wait times and utilization. It solves problems related to optimizing system design, comparing queueing strategies, and meeting service targets. The tool takes in system parameters as inputs and outputs theory-backed metrics, schedule insights, and stability checks to inform decision-making.

Canonical page: https://skillsregistry.net/skills/kiyoung8-simulation-by-simpy-mcp  
JSON: https://api.skillsregistry.net/v1/skills/kiyoung8-simulation-by-simpy-mcp

## Description

Simulate M/M/1, M/M/c, and manufacturing (MPS) systems to forecast wait times, utilization, and makespan. Compare separate versus pooled queues and get parameter recommendations to meet service targets. Analyze results with theory-backed metrics, schedule insights, and clear stability checks.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** monitoring
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/kiyoung8/simulation_by_simpy_mcp)
- **Repository:** <https://github.com/kiyoung8/Simulation_by_SimPy_MCP>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kiyoung8-simulation-by-simpy-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kiyoung8-simulation-by-simpy-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kiyoung8-simulation-by-simpy-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt