MCP 服务器
开放的 Model Context Protocol 服务器注册表。按类别、传输方式或使用场景,为 AI 智能体寻找合适的工具、资源和提示词。
部分描述为试点机器翻译内容,尚未经过人工审核。
服务器
177
工具
471
类别
11
贡献者
155
通过 Model Context Protocol 安全访问本地文件系统。AI 智能体可以在可配置的访问控制下读取、写入、搜索和管理文件及目录,支持读取文件内容、创建目录、移动文件以及使用 glob 模式搜索。
MCP server for Dropbox cloud storage. Lets AI agents list folders, upload and download files, search content, move and delete items, and create shared links via the Dropbox API with OAuth. Useful for document workflows, backups, and giving agents access to files stored in Dropbox.
Official Box MCP server for enterprise content management. Lets AI agents search files, read documents, extract text and metadata, ask questions with Box AI, and manage folders via the Box API. Useful for document analysis, knowledge retrieval, and automating content workflows over files stored in Box.
Reference MCP server for Git repository operations. Provides tools to read, search, and manipulate Git repositories including viewing commit history, diffs, branches, file contents at specific revisions, and repository status. Enables AI agents to understand code changes and navigate version history without direct filesystem access.
GitHub 官方 MCP 服务器,可将 AI 工具直接连接到 GitHub 平台。AI 智能体可以管理代码仓库、issue、pull request、分支、文件、GitHub Actions 工作流和代码安全。支持远程 OAuth 模式和本地 Docker 或二进制模式,并可精细配置工具集。
Official Figma MCP server that brings design context directly into AI coding workflows. Provides tools for extracting design information, generating code from Figma selections, taking screenshots, creating and editing Figma files, generating diagrams from Mermaid syntax, searching design systems, managing Code Connect mappings, and uploading assets. Supports both remote (OAuth) and local (desktop app) server modes.
Official GitLab MCP server connecting AI tools to GitLab's DevOps platform. Enables agents to manage projects, issues, merge requests, branches, files, CI/CD pipelines, and the GitLab Duo workflow. Supports both GitLab.com SaaS and self-managed instances with fine-grained access tokens.
MCP server for DuckDB, the fast in-process analytical database. Lets AI agents run analytical SQL over local files (CSV, Parquet, JSON), attach databases, inspect schemas, and profile queries. Ideal for ad-hoc data analysis, ETL prototyping, and querying large columnar files without a separate database server.
MCP server for the Telegram Bot API. Lets AI agents send messages, deliver files and photos, and read updates from chats and channels through a bot, enabling notifications and conversational workflows from AI-powered tools.
E2B's MCP server gives AI agents the ability to run arbitrary code in secure, isolated cloud sandboxes. Each sandbox is a fast-booting micro-VM where models can execute Python and shell commands, install packages, read and write files, and capture stdout/stderr — ideal for code interpretation, data analysis, and agentic workflows that need real execution.
A Model Context Protocol server for Google Drive that lets AI assistants list, search, and read files stored in Drive, with automatic export of Google Docs, Sheets, Slides, and Drawings to readable formats. Authenticates via OAuth 2.0 and exposes Drive files as MCP resources so agents can ground their answers in your documents without copying data into chat first.
Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.
MCP server for interacting with a Tinybird Workspace from any MCP client. Lets AI agents explore data sources, call published API endpoints, run SQL queries over real-time data, and push datafiles, making Tinybird's analytics readily available to LLM-driven workflows.
Official Apple Xcode MCP server (xcrun mcpbridge) that gives external AI agents direct access to Xcode IDE capabilities. Provides 20 native tools for building projects, running tests, reading and writing files in the project navigator, searching code with regex, rendering SwiftUI previews, executing code snippets, browsing Apple Developer documentation, and inspecting build logs and workspace issues. Requires Xcode 26+ with MCP enabled in Intelligence settings.
Skills 与 MCP 服务器
有什么区别?Skills定义“做什么”
Skill 将说明、示例提示词和推荐模型组织在一起,让智能体稳定地完成任务。Skills 增加的是知识,而不是新的连接。
MCP 服务器定义“如何连接”
MCP 服务器通过连接数据库、API 和文件等真实系统,为智能体增加新能力。MCP 提供连接和操作,而不是任务说明。
简单来说:当模型需要把某项任务做好时选择 Skill;当模型需要访问工具或系统时选择 MCP 服务器。两者可以组合使用,Skill 可以依赖 MCP 服务器提供的工具。
开发了 MCP 服务器?
将它提交到由社区维护的开源注册表。