# forgemcp

> forgemcp — dregen612-forgemcp. Use this tool when you need to manage and deploy MCP infrastructure for AI agents, providing them with production-ready tools and integrating with git for seamless version control. It solves problems of infrastructure setup and maintenance, allowing for efficient deployment of AI models. Ideal for use cases requiring scalable and reliable AI agent environments.

Canonical page: https://skillsregistry.net/skills/dregen612-forgemcp  
JSON: https://api.skillsregistry.net/v1/skills/dregen612-forgemcp

## Description

Managed MCP infrastructure — give your AI agents production-ready tools

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** scanned
- **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/Dregen612/forgemcp)

## 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": "dregen612-forgemcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dregen612-forgemcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dregen612-forgemcp/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