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MCP Sncf

全面解析MCP SncfMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器，MCP Sncf能让AI助手访问实时数据、执行操作，为您提供更智能的工作体验和自动化解决方案。

Enables Claude to control Spotify features including playback control, playlist management, search, and accessing user's listening history and preferences through the Spotify API.

Enables AI agents to establish and manage persistent SSH connections to remote hosts for executing commands. Supports SSH config files, multi-host management, and automatic reconnection with thread-safe concurrent operations.

A Node.js-based MCP server that extracts numbers from text and generates statistical chart data such as bar, pie, and line charts based on frequency. It enables AI agents to perform data extraction and visualization tasks through the Model Context Protocol.

MCP Std Server

Minimum requirements for LLM

Enables comprehensive management of Storyblok CMS through natural language interactions. Supports story creation and publishing, asset management, component schema updates, release workflows, and content discovery across all major Storyblok APIs.

An MCP server that enables users to interact with local documents for educational purposes through tools for listing and reading files. It features an integrated agent capable of automatically generating document summaries and study flashcards.

Enables hierarchical task planning and execution through recursive code and analysis subagents. Provides a planner tool that decomposes complex tasks and delegates them to specialized subagents with session-aware persistence.

This Model Context Protocol server enables AI assistants to interact directly with Ansible, allowing them to execute playbooks, manage inventory, check syntax, and perform other Ansible operations.

Advanced Model Context Protocol server that integrates Gemini AI with Tailwind CSS, providing intelligent component generation, class optimization, and cross-platform design assistance across major development environments.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

A template for building Model Context Protocol servers that allow AI assistants to interact with custom data and services through queryable resources and specialized tools.

A Model Context Protocol server that enables LLMs to interact with user and task data through JSON-RPC, offering tools like user management, task creation, and search functionality.

MCP Todo 0036bc96

API de gerenciamento de tarefas via WebSocket com execução modular de comandos e suporte a ferramentas, desenvolvida em TypeScript com banco SQLite. Projetada para integração com agentes de inteligência artificial.

Enables time tracking and reporting through Toggl Track integration with intelligent caching. Supports starting/stopping timers, generating daily/weekly reports, and managing projects with structured JSON output for automation workflows.

A Model Context Protocol server providing tools for DB queries, API calls, file I/O, and text transformations, enabling AI agents like Claude to perform real-world actions.

A Model Context Protocol server enabling AI assistants to interact with TriliumNext notes, providing tools for creating, searching, reading, and updating notes in your knowledge base.

Implementation of the Model Context Protocol for Unity Editor, allowing AI assistants to interact with Unity projects through a Node.js server bridge.

Enables AI assistants to interact with Unity Editor through the Model Context Protocol, allowing natural language control of Unity projects including scene manipulation, GameObject creation, component updates, package management, and test execution.

Enables AI assistants to analyze Java and Web projects, automatically generate unit tests (JUnit) and end-to-end tests (Selenium), and execute them directly through Maven or NPM commands.