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
MCP server for the Railway deployment platform. Lets AI agents create projects and services, deploy from repositories, manage environment variables, view deployment logs, and inspect service status. Useful for provisioning backends, databases, and cron jobs and for debugging deploys directly from an AI assistant.
Official SonarQube MCP server that brings code quality and security analysis into AI workflows. Lets agents fetch project issues, security hotspots, quality-gate status, and metrics from SonarQube Server or SonarCloud, so code health can be inspected and triaged conversationally.
Official MCP server for the Milvus vector database. Lets AI agents create collections, insert vectors, and run similarity and scalar-filtered searches over large-scale embedding data, enabling retrieval and long-term memory for AI applications.
Official Linear MCP server for project management integration. Enables AI agents to find, create, and update issues, projects, and comments in Linear. Supports searching issues by status, assignee, or label, creating new issues with full metadata, and managing project workflows directly from AI-powered development environments.
MCP server for the Wolfram Alpha computational knowledge engine. Gives AI agents access to step-by-step math, symbolic computation, unit conversions, scientific data, and curated facts across physics, chemistry, finance, and more. Useful for grounding quantitative answers and offloading precise computation from the model.
Official CircleCI MCP server. Lets AI agents fetch build and pipeline status, retrieve failed build logs, and diagnose flaky or broken jobs so developers can fix CI failures without leaving their AI-powered tools.
Official Elastic MCP server that connects AI agents to Elasticsearch data using the Model Context Protocol. Enables natural language interactions with Elasticsearch indices — querying, analyzing, and retrieving data without custom APIs. Supports both stdio and streamable-HTTP transports, and works with Elasticsearch 8.x/9.x clusters including Elasticsearch Serverless. Distributed as a Docker container image from the Elastic registry.
Official DigitalOcean MCP server for managing cloud infrastructure. Lets AI agents deploy and manage App Platform apps, Droplets, databases, and Spaces object storage, and read logs and metrics. Useful for provisioning and operating cloud resources and debugging deployments through an AI assistant.
Official monday.com MCP server. Lets AI agents read and update boards, items, and columns, create new items, and run queries against the monday.com Work OS so teams can manage work directly from AI-powered tools.
Official PagerDuty MCP server for incident management. Lets AI agents list and triage incidents, acknowledge and resolve them, look up on-call schedules, and query services so responders can manage operational incidents from AI-powered tools.
通过 Model Context Protocol 提供对 PostgreSQL 数据库的只读访问。AI 智能体可以检查数据库模式、执行 SELECT 查询并探索表结构。通过只读事务隔离防止意外修改数据。该服务器原属于参考服务器集合,现已归档并可在 servers-archived 中获取。
Provides browser automation capabilities through the Model Context Protocol using Puppeteer. Enables AI agents to navigate web pages, take screenshots, click elements, fill forms, and execute JavaScript in a browser context. Useful for web scraping, testing, and interacting with web applications programmatically. Originally part of the reference servers, now archived and available in servers-archived.
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 Plaid MCP server for financial data connectivity. Lets AI agents work with Plaid's APIs to retrieve accounts, balances, and transactions, and to build and debug integrations for banking, payments, and identity. Useful for fintech development, personal finance tooling, and automating account data workflows.
MCP server for Langfuse, the open-source LLM observability and prompt management platform. Enables AI agents to fetch and render managed prompts, list prompt versions, and query traces, helping teams manage prompts and inspect LLM application behavior from AI-powered tools.
MCP server for Hacker News. Lets AI agents fetch top, new, best, Ask HN, and Show HN stories, read comment threads, and look up items and users via the official Firebase API. Useful for tracking tech trends, summarizing discussions, and research into what the developer community is talking about.
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.
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.
MCP server for Jenkins CI/CD. Enables AI agents to trigger builds, inspect job and build status, stream console logs, and diagnose failing pipelines, bringing continuous integration workflows into AI-powered development environments.
Official LaunchDarkly MCP server for feature management. Lets AI agents create and toggle feature flags, manage targeting rules and segments, and inspect flag status across environments. Useful for progressive delivery, kill switches, experimentation, and automating flag lifecycle from an AI assistant.
MCP server for Zendesk Support. Lets AI agents search and read tickets, add comments and replies, update ticket status and fields, and query help-center articles. Useful for building support copilots, triaging and summarizing tickets, and drafting grounded responses from an AI assistant.
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。