"Uptime Kuma" matching MCP servers:

Enables managing Uptime Kuma monitoring through natural language, including creating, editing, pausing, and deleting monitors, plus retrieving heartbeats, status, metrics, notifications, and status pages.

MCP server for Exit1 uptime monitoring. Enables AI assistants to create and manage uptime checks, configure alerts, and query status via natural language.

MCP server for uptime monitoring, incidents, alerting, and dependency status.

Enables searching for and checking the reachability of MCP servers through real handshakes and uptime verification.

MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor.

Provides unified access to multiple homelab services including Nginx Proxy Manager, Pi-hole, Uptime Kuma, Portainer, and UPS NUT for monitoring, management, and automation through a single modular interface.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

Independent latency and uptime data for 46 hosted AI inference APIs, probed every 5 minutes from 4 regions with no gateway, plus a verified model deprecation calendar and Claude Code / Codex speed and accuracy drift. Four read-only tools, no API key; data CC BY 4.0.

Enables agents to inspect app status, uptime, response times, incidents, and certificate/domain expiry; set up and manage monitors and status pages; and draft incident updates through authenticated MCP tools.

Uptime monitoring from your AI agent: create and diagnose checks (40 types: HTTP, TCP, DNS, SSL, ICMP, databases, message queues and more), read results and incidents, and manage status pages and maintenance windows. Built into the self-hostable SolidPing server, served over streamable HTTP at /api/v1/mcp.

Enables AI assistants to query KumoRFM for predictive analytics on relational data, including graph management, natural language to PQL conversion, and training-free predictions.

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

Provides professional-grade data center engineering calculations including cooling, power, GPU thermal optimization, UPS/battery sizing, tier classification, and commissioning workflows, compliant with ASHRAE and Uptime Institute standards.

Enables MCP clients to query an organisation's merged-PR history as a FalkorDB graph, computing bus factor, module risk and successor candidates with the evidence path behind each answer. It also forks the graph to simulate a person's departure, hand a plan through analyst, planner and reviewer roles, and draft reviewable succession artifacts such as CODEOWNERS patches and issues.

Enables Claude Desktop to interact with KURA Notes API for semantic search, note creation, retrieval, and management. Supports natural language queries to search, create, retrieve, list, and delete notes with metadata like titles, tags, and annotations.

Find the most reliable AI agent for any task. Search 2,000+ agents across A2A and MCP with quality filters — min uptime, max latency, score thresholds. Check if an agent is alive before routing to it. Like Artificial Analysis, but for agent services.

A FastMCP-based tool for monitoring server statistics that retrieves CPU, memory, and uptime information from both local and remote servers via SSH.

MCP server for Uptimepage uptime monitoring. An LLM client can read your monitors and incidents, run a check on demand, and post incident updates. Writes need an OAuth login and a scoped token, and each one is logged.

Adds image understanding to AI coding clients that lack native vision, letting them analyze screenshots, error messages, UI mockups and documents through a unified image_understand tool. Supports multiple vision LLM providers with automatic cropping, compression and retry handling.

Validates and rewrites AI-generated text to match brand voice, supporting REST API, MCP, CLI, and GitHub Actions.

Enables beginners to explore GitHub repositories and issues, assess issue suitability based on their skills and experience, and generate step-by-step contribution roadmaps through an MCP-compatible AI assistant.

Adds image understanding to AI assistants that lack native vision, letting them analyze code screenshots, error captures, UI layouts, documents, and OCR content through a single unified image_understand tool. It routes requests across multiple vision model providers such as GLM-4.6V, DeepSeek-OCR, Qwen3-VL, Doubao-Seed, and Hunyuan, handling large-image cropping, compression, retries, and HTTP/Docker deployment.

Provides a unified image-understanding tool for AI coding assistants without native vision, letting them analyze screenshots, error messages, UI layouts, and documents through multiple vision LLM providers. Supports local files, remote URLs, and Data URIs with preprocessing, OCR, multi-crop, retries, and HTTP/Docker deployment.

A multi-model vision MCP server that gives image understanding to AI coding assistants lacking native vision, letting them analyze screenshots, error messages, UIs, and documents through a single image_understand tool. It routes requests to major vision LLM providers such as GLM, DeepSeek-OCR, Qwen-VL, Doubao, and Hunyuan, with automatic image preprocessing, cropping, and retries.

Enables AI coding assistants without native vision to analyze images — screenshots, error messages, UI layouts, and documents — through a single image_understand tool. It routes requests across multiple vision LLM providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan, or any OpenAI-compatible endpoint), with automatic cropping, compression, and retry handling for text-dense or large images.

Enables AI agents to browse curated city event feeds, retrieve full details for individual events, and list an organizer's public calendar without authentication. It returns only public event metadata, stripping attendee, guest, host, and manager data before responding.

Gives AI coding models without native vision the ability to analyze images — screenshots, error messages, UI mockups, and documents — through a single unified image understanding tool. It routes requests to multiple vision model providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan, or any OpenAI-compatible endpoint) with automatic cropping, compression, OCR-friendly handling, and retries.

Enables AI coding clients that lack native vision to analyze screenshots of code, errors, UIs, and documents by routing images through a single image_understand tool backed by multiple vision LLM providers such as GLM-4.6V, DeepSeek-OCR, Qwen3-VL-Flash, Doubao-Seed, and Hunyuan-Vision. Handles local files, remote URLs, and Data URIs with automatic multi-crop, compression, retry, and OCR-friendly preprocessing, and can be deployed over stdio or shared HTTP/Docker for multiple clients.

Enables AI clients and coding models that lack native vision to analyze images — screenshots, error captures, UI mockups, documents and OCR — through a single unified image-understanding tool. Routes requests to multiple vision model providers (GLM, DeepSeek-OCR, Qwen, Doubao, Hunyuan or any OpenAI-compatible endpoint) with automatic cropping, compression and retry handling.

Enables AI assistants without native vision to analyze screenshots, code errors, UI, documents, and OCR images by routing requests to multiple vision model providers. It supports a unified image-understanding tool with local files, remote URLs, and Data URIs.