# mesh-studio

> mesh-studio — mrodgersjs-web-mesh-studio. Use this tool when you need to manage and control multi-node AI subsystems, ensuring reliable deployment, monitoring, and recovery of inference fleets. It solves problems related to scalability, reliability, and security of AI deployments, providing a unified interface for Docker, Kubernetes, and self-hosted environments. With mesh-studio, you can input configuration and monitoring data, and output proof of deployment and system health, streamlining AI subsystem management.

Canonical page: https://skillsregistry.net/skills/mrodgersjs-web-mesh-studio  
JSON: https://api.skillsregistry.net/v1/skills/mrodgersjs-web-mesh-studio

## Description

Fleet control plane — probe, boot, recover multi-node AI subsystems with proof. Docker, Kubernetes, self-hosted inference fleet management.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/mrodgersjs-web/mesh-studio)

## 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": "mrodgersjs-web-mesh-studio"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mrodgersjs-web-mesh-studio` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mrodgersjs-web-mesh-studio/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