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

AI sysadmin for Home Assistant that provides entity health analysis, automation diagnostics, dashboard analysis, configuration search, and system health scoring via the Model Context Protocol.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Enables AI assistants to monitor and analyze industrial process data from DCS/SCADA systems via MCP protocol, with domain expert knowledge for anomaly detection and recommendations.

Enables LLMs to query real job data and summarize backend job failures using MCP tools backed by a SQLite database.

Enables agents to interact with a GlitchTip instance for issues, events, projects, releases, alerts, uptime monitors, performance, and more via stdio or HTTP.

A read-only Kubernetes MCP server that enables developers to inspect app status, view pod events, and fetch container logs from dev clusters without requiring full kubectl access.

Asynchronous MCP server for unified multi-platform network infrastructure management, providing 97 tools across 10 connectors including SSH, MikroTik, Palo Alto, Aruba, Graylog, LibreNMS, Cisco APIC/NDFC, and Panorama.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

Enables troubleshooting of LDAP directory services through natural language queries, providing health diagnostics, replication status, performance metrics, log analysis, and configuration comparisons across multiple servers.

Enforces identity-based access control and audit logging for MCP servers, letting you grant fine-grained tool permissions to users and systems while failing secure by default.

MCP server that connects LLMs to Kubernetes clusters for troubleshooting, scanning failing pods, diagnosing root causes, and applying guarded fixes or generating manifests via natural language.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

Provides comprehensive logging and monitoring capabilities for MCP services with real-time log tailing, advanced search, error analysis, and anomaly detection. Enables centralized log aggregation, correlation tracking, and health monitoring across all MCP ecosystem services.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Read-only MCP server for querying ClickHouse (product telemetry) and Elasticsearch (download analytics), built for Percona VISTA.

Enables observability and governance for local LLMs via Ollama, including auditing model usage, scanning prompts for secrets/PII, and enforcing allow/deny policies.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.

An enterprise AI control plane with an MCP gateway for connecting agents to tools, enforcing identity-based access and security policies, and recording activity.

Connects AI-powered tools to the Confident AI platform for evaluating, observing, and iterating on AI quality, enabling cloud evaluations, dataset management, prompt versioning, production tracing, and human annotations directly from editors like Cursor and Claude Code.

Enables Claude Code to query fleet telemetry data for device health summaries, anomaly detection, capacity breach forecasts, and incident history via narrow MCP tools.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

Enables AI agents to analyze, cluster, compare, and export reports from local log files through seven read-only tools, returning compact evidence packs with line-number citations instead of raw log dumps. All processing happens on the local machine, so log data never leaves the environment.

Enables AI assistants to query system health, metrics, service reconnaissance, run multi-node patrols, and send incident alerts across distributed infrastructure through MCP tools.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Compresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.

MCP server that exposes AI credit usage data from OpenMeter to the TAIS AI chat service, automatically scoped to the calling tenant and restricted to admin users.

Read-only MCP server for querying AI usage metrics (exact tokens, cost, latency, errors, productivity) from a local SQLite database, enabling charts and analysis in Claude Code and Cursor.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.