# AT Bridge

> Use this tool when you need to debug IoT modules and interact with chip platforms using AT commands. The AT Bridge enables AI assistants to send commands over serial ports, leveraging a built-in knowledge base for efficient troubleshooting. Ideal for use cases requiring low-level module debugging and testing, it accepts AT commands as input and returns responses for further analysis.

Canonical page: https://skillsregistry.net/skills/zeng-andrew-at-bridge  
JSON: https://api.skillsregistry.net/v1/skills/zeng-andrew-at-bridge

## Description

MCP server that enables AI assistants to debug IoT modules by sending AT commands over serial ports, with a built-in knowledge base for chip platform commands.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/waino6jvpl)
- **Repository:** <https://github.com/zeng-andrew/at_bridge>

## 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": "zeng-andrew-at-bridge"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zeng-andrew-at-bridge` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zeng-andrew-at-bridge/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