"Using AI to control and access data from Home Assistant and smart home devices" matching MCP servers:

A Model Context Protocol (MCP) integration that allows AI assistants to control Home Assistant devices by searching for entities and controlling devices through natural language commands.

Expose all Home Assistant voice intents through a Model Context Protocol Server allowing home control.

Enables control and monitoring of Home Assistant smart home devices through MCP protocol. Automatically manages authentication tokens and provides simplified tools for device discovery, switch control, and light brightness adjustment.

Enables comprehensive control and monitoring of Home Assistant smart home devices, automations, scenes, and system management through AI assistants. Supports lights, climate, media players, notifications, history tracking, and advanced automation workflows.

Enables autonomous AI agents to safely inspect, configure, and visually validate remote Home Assistant dashboards, automations, and scripts.

A storage-backed MCP server for sharing durable project context between trusted coding agents, with project discovery, optimistic concurrency, and timestamped handoffs.

Enables control of OXII smart home devices through the Model Context Protocol, supporting device switching, air conditioner control, cronjobs, and room scenarios. Integrates with chatbots and MCP-compatible clients for natural language home automation.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

MCP server that exposes Gmail and SAP tools, enabling natural-language email management and SAP data browsing through a Mistral-powered AI assistant.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Assists AI developers with intelligent requirement analysis and architecture design through guided clarification questions, branch-aware management, and automated architecture generation with persistent storage.

Enables AI agents to control Alexa-connected smart home devices, including voice announcements, music control, smart lighting, sensor monitoring, and volume management through the Alexa API.

Enables LLMs to discover and control Crestron Home automation systems through natural language, including lights, shades, scenes, thermostats, and sensors with multi-language support and fuzzy device name matching.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

A production-ready Model Context Protocol server implementation that connects AI assistants to the TON blockchain, allowing them to query wallet balances, transaction details, smart contracts, and other blockchain data.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Enables AI-powered research by breaking a topic into subtopics, gathering information via agents, and compiling a report. Integrates with LangGraph and RAG for orchestration and contextual retrieval.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.