productivity & workflow를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 9669개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Manages software projects with integrated tracking, note-taking, and GitHub synchronization.
Enables interaction with DingTalk through sending messages, retrieving conversation and user information, and managing calendar events.
Manages Jira tickets using natural language commands or direct forms through a Streamlit interface with MCP integration.
Provides file statistics, directory listing, and image compression capabilities through a Model Context Protocol (MCP) server.
Enables AI assistants to interact with JIRA's Tempo time tracking system.
Provides an MCP server to integrate AI assistants with Fatebook for tracking personal predictions.
Provides a minimal MCP server for scanner capture, supporting ADF, duplex, page-size handling, batching, and multipage assembly.
Integrates AI assistants with your media automation tools, enabling natural language control over services like Sonarr, Radarr, and Plex.
Connects AI Endurance training platforms to AI assistants for conversational access to training data, workouts, and performance analytics.
Parse various document formats like PDF, Word, Excel, and PowerPoint to extract their content.
Enforces critical best practices and safety protocols for Claude AI, automatically preventing 96 documented failure patterns.
Empowers AI agents to interact with local code and data through an optimized Python-based Model Context Protocol server.
Empower AI agents with persistent, contextual memory to transform them into long-term, knowledgeable employees.
Connects AI assistants to your Nestr workspace for task management, organizational insights, and collaboration.
Empower local LLMs like Qwen3 with comprehensive coding agent capabilities through an MCP server.
Analyzes local photo libraries using computer vision models to provide technical insights for AI applications.
Enables headless Claude Code instances to interact with users through OpenClaw-connected messaging apps like Telegram, Signal, and Discord.
Integrates fully offline text-to-speech and speech-to-text capabilities into coding assistants via the Model Context Protocol (MCP).
Automates the creation of AGENTS.md files by analyzing codebases with tree-sitter, providing AI clients with structured project context.
Empowers AI coding agents with a self-correction engine to learn from failures and prevent recurring mistakes across sessions.
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