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MCP-AWS EC2 Manager

MCP Server

AI‑powered AWS EC2 instance control from the terminal

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Updated Apr 7, 2025

About

MCP-AWS is an AI agent server that lets users provision and terminate AWS EC2 instances using natural language commands. It integrates with OpenAI Agents via a custom MCP server exposing EC2 start/stop tools.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

MCP-AWS Demo

MCP-AWS is an AI‑driven MCP server that bridges natural language commands with AWS EC2 management. By exposing two core tools— and —the server lets OpenAI Agents or other MCP clients create and tear down EC2 instances without writing code. This addresses a common pain point for developers: the need to manually interact with AWS consoles or CLI tools when prototyping, testing, or scaling infrastructure. With MCP-AWS, a simple prompt like “Create an EC2 instance” is translated into a fully authenticated API call that provisions the machine, returning its ID for further use.

The server’s value lies in its seamless integration with existing AI workflows. Developers can embed the MCP-AWS server into larger agent pipelines, chaining provisioning steps with configuration management, deployment scripts, or monitoring tasks. Because the MCP server follows the standard protocol, any client that understands MCP can invoke its tools, making it a drop‑in component for automated CI/CD pipelines or chatbot interfaces that require on‑demand compute resources.

Key capabilities are delivered in plain language:

  • Provisioning: Specify instance type, AMI ID, key pair, and security groups, and the server handles all API calls to launch the machine.
  • Termination: Pass a running instance’s ID, and the server will safely shut it down, freeing resources.
  • Security: All operations run under an IAM role defined by the environment, ensuring least‑privilege access and auditability.
  • Extensibility: The MCP server can be expanded with additional tools (e.g., tagging, monitoring) or integrated into other cloud platforms using the same protocol.

Real‑world scenarios that benefit from MCP-AWS include automated testing environments where a CI job spins up fresh instances, on‑demand training workloads that require temporary GPU nodes, or chatbot assistants for DevOps teams that can provision resources with a simple voice or text command. The server also serves as an educational platform for learning how MCP servers can be paired with OpenAI Agents to create intelligent, cloud‑aware assistants.

In summary, MCP-AWS demonstrates how a lightweight MCP server can unlock powerful, programmatic control over AWS EC2 resources through natural language. It provides developers with a secure, reusable interface that fits naturally into AI‑driven toolchains and accelerates infrastructure automation.