# tinymcp

> tinymcp — golioth-tinymcp. Use this tool when you need to control embedded devices using large language models (LLMs) via the Model Context Protocol. It solves problems related to integrating AI models with physical devices, enabling seamless interaction and automation. The tinymcp tool takes LLM inputs and outputs device control signals, making it ideal for IoT and robotics applications.

Canonical page: https://skillsregistry.net/skills/golioth-tinymcp  
JSON: https://api.skillsregistry.net/v1/skills/golioth-tinymcp

## Description

Let LLMs control embedded devices via the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/golioth/tinymcp)

## 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": "golioth-tinymcp"
    }
  }
}
```

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

---
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