# agentpack

> agentpack — selvaonline-agentpack. Use this tool when you need to streamline AI agent team management and deployment. Agentpack solves the problem of manually setting up and supervising AI agent teams by providing a comprehensive solution that includes a LangGraph supervisor, live network UI, and auto-generated MCP server. It takes a single YAML file as input and outputs a fully functional AI agent team setup, ideal for use cases where efficient team management and evaluation are crucial.

Canonical page: https://skillsregistry.net/skills/selvaonline-agentpack  
JSON: https://api.skillsregistry.net/v1/skills/selvaonline-agentpack

## Description

Define your AI agent team in one YAML file — get a LangGraph supervisor, a live network UI, an auto-generated MCP server, and a behavioral eval harness. TypeScript, batteries included.

## Trust

- **Trust score (0–1):** 0.70
- **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/selvaonline/agentpack)

## 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": "selvaonline-agentpack"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/selvaonline-agentpack` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/selvaonline-agentpack/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