# mcp-go

> mcp-go — dwrtz-mcp-go. Use this tool when you need to integrate Model Context Protocol (MCP) functionality into your Go applications, solving problems related to model management and deployment. It provides an SDK for interacting with MCP models, accepting inputs such as model configurations and outputting optimized model deployments. Ideal for use cases involving machine learning model integration and automation, leveraging git for version control.

Canonical page: https://skillsregistry.net/skills/dwrtz-mcp-go  
JSON: https://api.skillsregistry.net/v1/skills/dwrtz-mcp-go

## Description

Model Context Protocol SDK for Go

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/dwrtz/mcp-go)

## 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": "dwrtz-mcp-go"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dwrtz-mcp-go` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dwrtz-mcp-go/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