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
Official MCP server for interacting with MongoDB databases and MongoDB Atlas. Enables AI agents to query collections, run aggregations, manage indexes, inspect schemas, and perform CRUD operations. Also supports Atlas cloud management including cluster provisioning, database user management, performance advisor, and stream processing. Supports read-only mode for safe exploration.
AgentMail MCP gives AI agents secure email operations through hosted MCP access and local stdio bridges for agent-native inbox workflows.
Apollo's official MCP server that exposes GraphQL operations as MCP tools, letting AI agents interact with any GraphQL API through the Model Context Protocol. Turns curated GraphQL operations into callable tools, supports schema introspection, and can run locally alongside a graph via the Rover CLI or in production with the Apollo Runtime Container.
Directus' MCP integration connects agents to headless CMS data, schemas, and operations for governed content and application workflows.
HashiCorp's official MCP server for Consul, providing integration with the Consul API for service discovery, configuration management, and service mesh operations. Lets AI agents list registered services and their health, read and write KV configuration entries, and inspect mesh intentions and config entries.
Google's MCP Toolbox provides secure, ready-made and custom tools for database queries, schema operations, and semantic search in agent workflows.
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.
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.