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

4 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
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
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
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

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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