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
175
Tools
465
Categories
11
Contributors
153
Provides access to AWS documentation and service information through the Model Context Protocol. Enables AI agents to search AWS documentation, retrieve service descriptions, look up API references, and find best practices for AWS services. Part of the official AWS Labs MCP servers collection with multiple AWS-focused servers available.
Enables AI agents to interact with Amazon Web Services through the Model Context Protocol. Provides access to core AWS services including S3, Lambda, DynamoDB, CloudWatch, and IAM. Supports resource discovery, log analysis, and infrastructure management with proper credential handling and region awareness.
Provides AI agents with the ability to manage Terraform infrastructure through the Model Context Protocol. Supports plan generation, state inspection, resource drift detection, and module discovery. Enables safe infrastructure changes with plan review before apply.
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.