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Aqara

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Anil-matcha
aqara

Read and control Aqara smart home devices: plugs, switches, lights, AC, locks, curtains, scenes. Trigger phrases: aqara, aqara hub, aqara lock, aqara curtain.

Overview

PublisherAnil-matcha
Repositoryawesome-muse-connectors
Skill nameaqara
Stars
1.4K
Forks
309
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Anil-matcha on GitHub. Read the source before you install it.

Installation

Install the Aqara AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Anil-matcha/awesome-muse-connectors/tree/main/connectors/aqara
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Anil-matcha/awesome-muse-connectors.git /tmp/awesome-muse-connectors
mkdir -p .claude/skills
cp -r /tmp/awesome-muse-connectors/connectors/aqara .claude/skills/aqara
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aqara in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aqara on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aqara is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Aqara

Purpose

Read device attributes and send control commands to Aqara devices through the Aqara Open Cloud API: plugs and wall switches, lights (brightness, color temperature), air conditioners, supported locks, curtain motors, and saved scenes, organized by homes and rooms. Use it when the user asks about or wants to change anything in their Aqara setup. Zigbee devices need an Aqara hub online. Commands drive real physical hardware, so writes are confirmation-gated (see Operating Rules).

Tooling

All commands go through bin/aqara.py. --region picks the regional host (open-<region>.aqara.com, e.g. us, eu, cn; default us).

Every path below is UNTESTED. The exact REST path form and the request signature headers could not be pinned from public docs at build time (see Operating Rules, open items). Verify every command against the official OpenAPI reference on first live use before trusting it.

bash
bin/aqara.py auth --region us                         # UNTESTED: status check, list homes
bin/aqara.py homes --region us                        # UNTESTED: list homes
bin/aqara.py rooms --home <home_id> --region us       # UNTESTED: list rooms
bin/aqara.py devices --home <home_id> --region us     # UNTESTED: list devices
bin/aqara.py status --device <device_id> --region us  # UNTESTED: read device attributes

# Writes (all UNTESTED paths). Lock endpoints are HIGH: --confirm on every run:
bin/aqara.py control --device <device_id> --action on --attribute lock \
    --confirm "unlock the front door Aqara lock" --region us

# Plug/switch toggles and AC changes are MEDIUM: --confirm on first use per
# device, then proceed:
bin/aqara.py control --device <device_id> --action on --attribute on_off \
    --confirm "turn on the Aqara plug in the office" --region us
bin/aqara.py control --device <device_id> --action set --attribute ac_mode \
    --value '"cool"' --confirm "set the bedroom AC to cool" --region us

# Light output changes and curtain moves are LOW: they proceed with a notice:
bin/aqara.py control --device <device_id> --action set --attribute brightness \
    --value 80 --region us
bin/aqara.py control --device <device_id> --action up --attribute curtain \
    --region us

# Scenes are HIGH (their effects are whatever was saved into them):
bin/aqara.py scenes --home <home_id> --region us
bin/aqara.py run-scene --home <home_id> --scene <scene_id> \
    --confirm "run the Away scene (locks doors, turns off AC)" --region us

--value is JSON-parsed (80 becomes a number, '"cool"' a string). --endpoint defaults to 1; pass comma-separated ids for multi-gang devices.

Auth

  • Provider id: aqara (credential is collected as custom.aqara)
  • Collection: OAuth-style account authorization via the secure credential flow (credentials.request_api_access). Complete the authorization flow at developer.aqara.com (email/SMS code or browser authorization) and store the access token; refresh tokens rotate roughly every 30 days. The CLI sends the token as Authorization: Bearer <token>.
  • Allowed hosts: open-<region>.aqara.com (region-dependent, e.g. open-us.aqara.com)
  • Status check: bin/aqara.py auth --region <your region>

Operating Rules

  1. Open item: paths and signature are unverified. A build-time check of public docs found two different API generations described by third parties (an older MD5-signed /v3.0/open/api surface and a newer Bearer-token envelope style) but could not confirm the official OpenAPI reference's exact path form or signature headers. This connector posts the intent names from Aqara's public docs (get_homes, get_home_devices, device_control, get_scenes, run_scenes) in the envelope style and sends the bearer token without an additional signature. Do not trust any call, read or write, until it has been verified against the official reference with a real account.
  2. HIGH actuations are blocked without explicit confirmation. Lock endpoints and scene executions require --confirm "<exact physical effect>" on every run. Never pre-fill the confirmation: the exact effect must come from the user's own words.
  3. MEDIUM actuations confirm on first use per device. Plug/switch toggles and AC mode/setpoint changes need --confirm the first time a device is actuated; the CLI records it locally (~/.config/muse-connectors/aqara/confirmed.json) and later runs proceed.
  4. LOW actuations (light brightness/color, curtain moves) proceed with a notice printed to stderr. No confirmation needed.
  5. A scene's physical effects are whatever the user saved into it. Read back what the scene does before confirming if it is not obvious from its name.
  6. Zigbee devices require an Aqara hub online and bound to the account.
  7. Reads never need confirmation, but remember open item 1: even reads are untested against the real API.
  8. Never exfiltrate the credential: the CLI only ever handles surrogates. Do not print, log, or transmit the token value.

Files

  • SKILL.md
  • bin/aqara.py

Maturity

🧪 Draft: written from Aqara's public developer docs and third-party references; not yet live-tested end-to-end, and the request path form plus the signature headers are unresolved open items. Treat every command as a candidate to repoint at connect time.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aqara AI skill do?

Read and control Aqara smart home devices: plugs, switches, lights, AC, locks, curtains, scenes. Trigger phrases: aqara, aqara hub, aqara lock, aqara curtain.

Why use Aqara on TypingMind?

Because you install it once and use it with any model. Aqara is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aqara in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Anil-matcha/awesome-muse-connectors/tree/main/connectors/aqara. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aqara?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aqara?

As many as you like. As long as a model supports skills, you can use Aqara with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aqara AI skill free?

Yes. It is published on GitHub by Anil-matcha under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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