# Drengr

> Use this tool when you need to extend AI agent capabilities to mobile devices, enabling them to interact with and perceive their environment through Android and iOS devices. Drengr solves problems of limited AI agent interaction with physical spaces, allowing for more immersive and interactive experiences. It takes in AI commands and outputs device interactions, such as camera and sensor data, to facilitate seamless human-AI collaboration.

Canonical page: https://skillsregistry.net/skills/dev-drengr-server  
JSON: https://api.skillsregistry.net/v1/skills/dev-drengr-server

## Description

Eyes and hands for AI agents on Android and iOS devices.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** unverified

## Facts

- **Version:** 0.1.6
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/dev.drengr%2Fserver)
- **Repository:** <https://github.com/SharminSirajudeen/drengr-community>

## 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": "dev-drengr-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dev-drengr-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dev-drengr-server/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