Servant
Home automation system. Extensible, integrable and smart.
Install / Use
claude mcp add ucpdh23 -- npx -y github:ucpdh23/ServantIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of Servant
Servant scores 65/100 on our quality scale, 2698th of 2,892 Automation skills we index.
Its MCP Server is 6.8 KB long, split into 7 sections and no code examples: a thorough specification that gives an agent plenty to work with.
It has 3 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated 21 days ago, so Servant is actively maintained.
- Our last check on 2026-09-06 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 87/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Servant compared with similar skills
All 4 of these similar skills score higher than Servant; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| Servant (this skill)by ucpdh23 | 65 | 3 | 21d ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 92.4k | 21d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.5k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.2k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 85.9k | today | MCP Server |
Frequently asked questions
- How do I install Servant?
- Run
claude mcp add ucpdh23 -- npx -y github:ucpdh23/Servant. The install tabs above show the steps for each supported agent. - Which AI agents does Servant work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is Servant safe to use?
- It is MIT-licensed and scores 87/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is Servant still maintained?
- The repository was last updated 21 days ago, so Servant is actively maintained.
Skill content
View source on GitHubServant
Smart Home Assistant Platform
Managing a household involves many small but important tasks: keeping your shopping list up to date, adjusting the heating system, maintaining control over your home calendar so you don't forget to pick up your child when they finish their music lessons, or monitoring some home automation events like temperatures, waterleaking sensors, devices in my wifi network or main door's status. Servant helps you take care of these recurring activities automatically and intelligently—so your home works with you, not against you.
Servant is your home assistant platform to simplify and automate domestic tasks efficiently.
Table of Contents
Introduction
Servant is a flexible and extensible home assistance platform designed to integrate seamlessly with sensors, actuators, and external systems. Unlike traditional solutions, Servant provides a customizable software architecture that adapts to your needs—whether it’s managing daily tasks, automating workflows, or enabling advanced AI-driven interactions.
Key Features
Modularity
Servant is composed for several modules. Each one corresponds to a logical subsystem. A module provides a set of functionalities provided as action calls and events subscription.
AI Capabilities
MCP implementation. Servant implements the Java SDK MCP server API, providing several Model Context Protocol (MCP) tools. This toolkit allows the integration of Servant in any GenAI Agentic system. The current implementation allows interaction with several modules of servant such as the shopping list, the calendar, temperature monitoring system and the notifications manager which facilitates (Telegram messages) messages publication. In future versions of Servant, new MCP tools will be provided with additional commands and actions.
Large Language Models (LLMs) offer a novel way to interact with your data. In addition to generating content from a given input, LLMs can be utilized to transform heterogeneous and irregular content into structured and more analyzable output. This transformed content can then be used to build a knowledge data model for future activities.
Interaction Human or machine interactions with Servant are possible through the pre-built interfaces:
-
Servant provides a RESTful API and integration to its messaging system through WebSockets. You can use these interfaces to build your own data consumer or data tracker agents in your preferred programming language.
-
Web interface that allows the creation of web applications.
-
Telegram chatbot as an asynchronous human/system interface.
-
Google Calendar integration to schedule and run actions at specific times.
-
VoIP interface which provides a conversational solution between the user and Servant.
Extensibility
Servant provides an extensible framework, implemented in Java and Kotlin, that allows the integration of new elements like sensors and actuators.
Integration of any kind of device into Internet of Things (IoT) technology is straightforward. Thanks to a distributed messaging system and Java, interfacing with any system to send or receive data from/to the cloud is never difficult. Integration with systems like IFTTT is supported.
Servant provides an MQTT interface to interact with sensors and external actuators. This solution is already integrated with a Zigbee2MQTT solution to connect to other systems.
Smart
-
Implementation based on two basic concepts: events and actions. It makes it easy to create advanced algorithms for devices to interact together (sensors and/or actuators) or with external systems.
-
Natural language processing for better human/system interaction.
-
Scheduler for automatic actions and event triggering.
-
Working on integration with OpenAI and a Neo4j knowledge database.
Additional Functionalities
Implementation Details
-
To simplify development, a Convention over Configuration policy has been adopted. This project implements and abstracts some concepts, providing a mini-framework to simplify development: - Provides an almost 99% friendly object-oriented static way to map and use JSON data. - Improved communication system inside the Vert.x nodes system using Java enum objects. - Toolkit to build state machines with a Java enums language. - Interaction between Java and Kotlin code.
-
Asynchronous JVM project (Java & Kotlin) based on Eclipse Vert.x
-
Built-in facilities on top of Vert.x Event Bus to handle interaction with events in a controlled way.
Requirements
- Java 21
- Linux-based system
Getting Started
- Clone the repository
- Ensure Java 21 is installed
- Build the project using Maven:
mvn compile - Configure your settings in the config file
- Run the application
Related Projects & Technologies
This project integrates with and builds upon several open-source technologies:
- Messaging & Communication: Eclipse Vert.x, MQTT, WebSockets
- Databases: MongoDB, Neo4j, SQLite
- AI & ML: OpenAI API, Model Context Protocol
- Smart Home: Zigbee2MQTT, MQTT
- External Services: Telegram Bot API, Google Calendar API, AWS SDK
- Build Tools: Apache Maven
License
See the LICENSE file for details.
Related Skills
Agent-Reach
92.4kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
headroom
74.5kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
CowAgent
47.2kOpen-source personal AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install.
Scrapling
85.9k🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl! Don't be shy, join here: https://discord.gg/EMgGbDceNQ and follow here for daily tips and tricks: https://x.com/Scrapling_dev
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
