"Checking the current time" matching MCP servers:

Provides a time_now tool to retrieve the current time, enabling time-sensitive queries in AI agents.

Integrates local FastMCP tools and multiple remote MCP services into Xiaozhi, providing calculator and current time utilities.

Enables LLM chat with routing and failover, balance checking, and model listing via MCP.

Let two AI agents build your app at the same time without stepping on each other by providing shared file locks, task delegation, and inter-agent communication.

Enables managing other MCP servers from within Claude Code, including wrapping for reliable restarts, listing, adding, removing, and checking health.

A TypeScript server implementing the Model Context Protocol (MCP) that provides datetime and timezone information to AI agents and chat interfaces, allowing them to access current time in various timezones.

An MCP server that runs concurrent, session-isolated Playwright browser contexts, so many agents can each drive their own browser at the same time without colliding.

Provides comprehensive weather information including current conditions, 7-day forecasts, and air quality data for any city worldwide using the Open-Meteo API. Features real-time weather data, hourly forecasts, sunrise/sunset times, and European Air Quality Index with human-readable descriptions.

This server integrates with the Ticketmaster API to provide AI agents with real-time concert and event data, enabling dynamic fetching and formatting for ease of interpretation.

A simple server that implements the Model Context Protocol, allowing AI models like Claude to fetch real-time weather information for any location using the wttr.in API.

Provides tools for AI assistants to interact with smart home devices through Home Assistant, allowing operations like checking entity states and calling services.

Enables MCP clients to interact with a local AI agent through Ollama, providing tools for checking weather, current time, and available models, while tracing calls to Langfuse.

Links IoT devices to AI large models using the MCP and MQTT protocols, enabling natural language control, real-time AI responses, and complex instruction execution for interconnected IoT devices.

Enables Large Language Models to access real-time data on Vilnius public transport stops and routes through the Model Context Protocol.

A lightweight messaging system that enables real-time communication between different AI agents through a shared, file-based message queue. It provides tools for sending, checking, and broadcasting messages to facilitate coordination across isolated project namespaces.

Enables AI agents to run a free AI-readiness audit of any URL, checking AI crawler rules, JavaScript-free page text, JSON-LD, llms.txt, sitemap, meta description, FAQ schema, and returning a score with findings and fixes. Also exposes the same capability via an A2A agent endpoint.

Delivers the LXAgents shared agent instruction set via MCP prompts and resources. It includes read-only tools for setting up and checking agent instructions in repositories.

Provides a multi-agent collaboration room with real-time messaging, file sharing, and coordination primitives for AI agents.

Enables intelligent task management, multi-agent workflows, and cross-IDE project management through the BMAD methodology, with features like time tracking, quality gates, and project templates.

Provides a remote MCP server with tools like guild_feed and join_guild for AI agents to interact with the Gold Rush Guild, an open activity feed. No installation or authentication required.