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

92

Tools

343

Categories

11

Contributors

79

CategoryAll18Database16Productivity14Development9DevOps8Research6AI6Cloud6Communication4Browser Automation3Security2Filesystem
TransportAllstdioSSEHTTP Streaming

3 servers

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GitLab MCP ServerGitLab

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.

2.1k ★
CircleCI MCP ServerCircleCI

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.

321 ★
Jenkins MCP ServerJenkins Community

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.

198 ★

Skills vs MCP servers

what's the difference?

Skillsthe “what to do”

A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.

MCP serversthe “how to connect”

An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. 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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