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
Popular community MCP server that gives AI assistants deep knowledge of n8n's workflow automation nodes, their properties, and operations, and can connect to a live n8n instance to create and manage workflows. Helps agents design, validate, and deploy automations correctly by exposing node documentation, validation, and workflow management tools.
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.
Official PayPal MCP server for commerce and payments. Lets AI agents create and capture orders, issue invoices, process refunds, manage subscriptions, and query transactions and disputes via the PayPal APIs. Useful for building checkout integrations, automating billing, and reconciling payments from an AI assistant.
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.
MindsDB's MCP integration gives agents access to AI workflows, data integrations, and automation capabilities through the MindHub platform.
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.
Built an MCP server?
Submit it to the registry — it’s open source and community-maintained.