AWS Resources MCP Server

The AWS Resources MCP Server is a lightweight, Docker‑ready implementation of the Model Context Protocol that lets AI assistants like Claude run arbitrary Python code against AWS services through boto3. By exposing a single dynamic resource () and a dedicated tool (), the server gives developers the flexibility to query, inspect, and even modify AWS resources directly from an AI workflow without leaving the chat interface. This solves a common pain point for teams that need to prototype or debug infrastructure changes quickly—no separate CLI, no manual SDK setup, just a prompt and a snippet of code.

The server’s value lies in its Python‑centric design. While other MCP offerings for AWS are often Node.js based or heavily restricted, this implementation runs in a fully sandboxed Docker container and relies on the battle‑tested boto3 library. Developers can contribute back in their native language, and the sandbox ensures that only a curated set of imports (boto3, operator, json, datetime, pytz) and built‑in functions are available, striking a balance between power and safety. The tool requires the user to set a variable, which the MCP framework captures and returns as structured data that an AI assistant can parse and respond to.

Key capabilities include:

• Dynamic AWS queries: Execute any boto3 code snippet, from listing S3 buckets to fetching the latest CodePipeline execution.
• Fine‑grained permissions: Operations are governed by the AWS credentials presented to the container, so users only see what their IAM role allows.
• Integrated AI workflow: The server’s resource and tool expose results directly to the assistant, enabling on‑the‑fly troubleshooting (e.g., resolving a DynamoDB permission error) or automated reporting.

Real‑world use cases span from dev‑ops automation—where an AI assistant can run to gather health metrics—to incident response—quickly fetching logs or resource states during an outage. The Docker image eliminates setup friction; teams can spin up a local instance or deploy it to an internal registry, keeping everything isolated and repeatable.

In summary, the AWS Resources MCP Server delivers a secure, Python‑friendly bridge between AI assistants and AWS. It empowers developers to write and run code against their cloud infrastructure within the same conversational context, dramatically speeding up troubleshooting, experimentation, and operational automation.