advanced-homeassistant-mcp: MCP server that gives AI assistants control over your Home Assistant

by jango-blockchained · MCP Server · ★ 56

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install advanced-homeassistant-mcp

git clone https://github.com/jango-blockchained/advanced-homeassistant-mcp.git
bunx github:jango-blockchained/advanced-homeassistant-mcp

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 78/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars56
Forks23
LanguageJavaScript
CategoryMCP Server
LicenseApache-2.0
Quality Score78/100
Open Issues1
Last Updated2026-06-14
Created2024-12-16
Platformsmcp, node
Est. Tokens~16k

About advanced-homeassistant-mcp

🏠 Home Assistant MCP Bridge the gap between AI assistants and your smart home 🚀 A powerful, secure, and extensible Model Context Protocol (MCP) server that enables AI assistants like Claude, GPT, and Cursor to seamlessly interact with Home Assistant. Control your lights, climate, automations, and more through natural language commands.

Compatible Skills

These tools work well together with advanced-homeassistant-mcp for enhanced workflows:

advanced-homeassistant-mcp alternative? Top 6 similar tools

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    AAHL's Agent Skills. 汇集了多种实用的智能体技能,涵盖Home Assistant智能家居控制、微软Edge TTS和智谱GLM-TTS文本转语音、DuckDuckGo搜索、DeepWiki文档检索、

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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