# go-mcp-anthropic-introduction

> go-mcp-anthropic-introduction — runaho-go-mcp-anthropic-introduction. Use this tool when you need to manage in-memory document storage and serve it over the Model Context Protocol (MCP) for applications requiring efficient data handling and completion handling. It solves problems related to document storage, retrieval, and completion, particularly in scenarios involving multiple prompts and resource templates. Ideal for use cases where a lightweight, Go-based MCP server is required, with inputs via stdio and outputs in a format suitable for MCP-compatible applications.

Canonical page: https://skillsregistry.net/skills/runaho-go-mcp-anthropic-introduction  
JSON: https://api.skillsregistry.net/v1/skills/runaho-go-mcp-anthropic-introduction

## Description

In-memory document store served over Model Context Protocol (stdio). Go rewrite of the Python mcp_server from Anthropic's MCP introduction, plus a completion handler, resource templates, and multiple prompts.

## Trust

- **Trust score (0–1):** 0.95
- **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/Runaho/go-mcp-anthropic-introduction)

## 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": "runaho-go-mcp-anthropic-introduction"
    }
  }
}
```

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