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

9 servers

Sort by
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
Xcode MCP ServerApple

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.

0
Memory MCP ServerAnthropic

Provides persistent memory capabilities through a knowledge graph stored in a local JSON file. Enables AI agents to create, read, update, and delete entities and their relationships. Useful for maintaining context across conversations, storing user preferences, and building structured knowledge bases that persist between sessions.

86.2k
Stripe MCP ServerStripe

Official MCP server for the Stripe API. Enables AI agents to interact with Stripe's payment infrastructure including creating and managing customers, payment intents, subscriptions, invoices, and products. Supports reading transaction data, handling refunds, and querying balance information. Useful for building payment integrations, debugging billing issues, and automating financial operations.

2.9k
Grafana MCP ServerGrafana Labs

MCP server for Grafana's observability platform. Enables AI agents to query metrics from Prometheus, search and analyze logs from Loki, query traces, list and manage dashboards, and investigate incidents. Useful for debugging production issues, building monitoring dashboards, and performing root cause analysis with AI assistance across the full Grafana LGTM stack.

2.1k
Resend MCP ServerResend

Integrates Resend email delivery service with AI agents through the Model Context Protocol. Enables sending transactional emails, managing email templates, tracking delivery status, and handling domains. Supports HTML and React Email templates for building beautiful transactional and marketing emails programmatically.

1.7k
Qdrant MCP ServerQdrant

Official MCP server for Qdrant vector search engine. Acts as a semantic memory layer enabling AI agents to store and retrieve information using vector similarity search. Supports storing text with metadata, semantic querying, configurable embedding models via FastEmbed, and both cloud-hosted and local Qdrant instances. Useful for building RAG pipelines, code search, knowledge bases, and long-term agent memory.

1.4k
Bitbucket MCP ServerAtlassian Community

MCP server for Atlassian Bitbucket that connects AI tools to repositories, pull requests, branches, and pipelines. Enables agents to review and create pull requests, read file contents and diffs, leave comments, and inspect build status on Bitbucket Cloud and Server.

410

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.

Built an MCP server?

Submit it to the registry — it's open source and community-maintained.

Submit on GitHub