MCP Servers

The open registry for Model Context Protocol servers. Find the right tools, resources, and prompts for your AI agents — filtered by category, transport, or use case.

Servers

206

Tools

545

Categories

11

Contributors

182

10 servers

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Asana MCP ServerAsana

Official Asana MCP server that connects AI tools to the Asana Work Graph. Enables agents to create and update tasks, manage projects and sections, add comments, search work, and summarize project status via a remote OAuth-secured endpoint.

760
Todoist MCP ServerDoist

MCP server for Todoist that lets AI agents create, update, complete, and query tasks using natural language. Supports projects, due dates, priorities, labels, and filters, making it easy to manage a personal or team task list conversationally.

720
ClickUp MCP ServerClickUp Community

MCP server for the ClickUp project management platform. Enables AI agents to create and update tasks, browse spaces, folders, and lists, and manage task status and assignees, bringing ClickUp work management into AI-powered tools.

645
Anthropic MCP ServerAnthropic

Official Anthropic MCP server providing direct access to Claude models through the Model Context Protocol. Enables AI agents to invoke Claude for sub-tasks like summarization, analysis, and code generation within agentic workflows. Supports system prompts, multi-turn conversations, and token counting. Updated for the MCP 2026-07-28 spec: a stateless request/response core that runs on serverless and edge infrastructure, a versioned extensions framework covering MCP Apps (interactive in-conversation UI) and Tasks (long-running work), and authorization hardened to align with production OAuth 2.0 and OIDC identity providers such as Entra and Okta.

4.5k
Trello MCP ServerTrello Community

MCP server for Trello that lets AI agents manage boards, lists, and cards. Supports creating and moving cards, updating due dates and labels, adding comments and checklists, and searching across boards, turning Trello into a conversational task and project tracker.

540
monday.com MCP Servermonday.com

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.

289
Sequential Thinking MCP ServerAnthropic

Provides a structured sequential thinking tool through the Model Context Protocol. Enables AI agents to break down complex problems into numbered thought steps, revise previous thoughts, branch into alternative paths, and adjust the total number of steps dynamically. Useful for multi-step reasoning, planning, and analysis tasks that benefit from explicit step-by-step thinking.

86.2k
Playwright MCP ServerMicrosoft

Microsoft's official Playwright MCP server that provides browser automation capabilities for AI agents. Enables navigating web pages, clicking elements, filling forms, taking screenshots, and extracting content. Supports headless and headed modes with Chromium, Firefox, and WebKit browsers. Ideal for web testing, scraping, and interactive browsing tasks.

33k
HubSpot MCP ServerHubSpot

Official HubSpot MCP server connecting AI tools to the HubSpot CRM. Enables agents to read and manage contacts, companies, deals, and tickets, search the CRM, and create engagements such as notes and tasks. Honors HubSpot scopes and rate limits via OAuth.

690
Heroku MCP ServerHeroku

Official Heroku MCP server that lets AI agents manage Heroku Platform resources. Supports listing and inspecting apps, scaling dynos, viewing logs, managing config vars and add-ons, and running one-off commands, so deployment and operations tasks can be handled conversationally.

480

Skills vs MCP servers

what’s the difference?

Skillsthe “what to do”

A skill packages know-how — instructions, an example prompt, and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.

MCP serversthe “how to connect”

An MCP server gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transport. MCP adds connections and actions, not task instructions.

Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.

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