"Information or definitions related to time" matching MCP servers:

An agentic AI system that answers time-related questions by calling a time API tool and general questions using an LLM, accessible through a simple chat interface.

Gives time-blind LLMs and agent frameworks a real clock: current time and timezone, elapsed task duration, countdowns to deadlines, timezone conversion, session heartbeats, cron-style due checks, and session-level timers. This lets locally hosted or self-built models stop hallucinating the time and actually perceive how long a task or conversation has been running.

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

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables MCP clients such as Claude Desktop to hand tasks to a running DeepSeek Harness window, where each task becomes a real session visible in the sidebar with a reusable session id. If the in-process plugin is unavailable, it falls back to running the task headless so the tool still returns a result.

Turns any OpenAPI/Swagger specification into a functional MCP server, dynamically exposing API endpoints as LLM tools or generating standalone Python code.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Enables agents to dynamically allocate test-time compute, including entropy-driven thinking token budgets, temperature annealing, and reflection passes, while verifying reasoning via MCTS search with process reward modeling, counterfactual backtracking, formal proof checking, and majority-vote consensus. Runs as a zero-dependency Python MCP server over STDIO JSON-RPC for integration with Claude Desktop, Cursor, or custom agent runtimes.

Enables agents to dynamically schedule thinking-token budgets, reflection passes, and temperature annealing while performing MCTS/process-reward verification, proof checking, and consensus voting through a standard-library STDIO MCP interface.

Enables enterprise work agents to decompose high-level business objectives into topological sub-tasks and directly synthesize final deliverables such as financial spreadsheets, executive presentations, and analytical reports.

Bridges Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) applications, allowing MCP clients such as Claude Desktop to discover and invoke ACP agents as tools and resources.

Enables two-model orchestration where Gemini in Google Antigravity delegates coding tasks to Qwen 3.8 Max in Qwen Studio Desktop via CDP, managing prompt delivery, file generation, continuation, and verification.

Enables AI agents to manage Kanban boards, cards, sessions, and automations through a unified MCP interface with real-time updates, supporting delegation, agent sessions, and human-in-the-loop interactions.

A full-stack template for building Model Context Protocol (MCP) servers with a modern React frontend, allowing developers to create AI agent tools and workflows while providing a beautiful web interface.

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

Acts as a proxy between a local Stdio connection and a remote Model Context Protocol server running over Server-Sent Events. It specifically enables Stdio-based MCP clients to connect to the SwiftZilla remote SSE endpoint.

An open source registry and proxy that federates MCP, A2A, and REST/gRPC APIs with centralized governance, discovery, and observability. It optimizes agent and tool calling, and supports plugins.

Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

An MCP server that gives AI agents fast access to verified EVM chain information, including RPC URLs, chain IDs, explorers, and native tokens.

A Model Context Protocol server that provides real-time Caltrain schedule information, allowing AI assistants to look up train departures between any stations and access station information using GTFS data.

Provides real-time oversight for Claude Code by connecting it to an OpenClaw agent that reviews, approves, blocks, or modifies actions before they execute.

MCP server that scores text, web pages and MCP tool definitions for prompt injection and tool poisoning.