MCP S3, developed by Txn2, is a free MCP server built with Go. It enables AI assistants to interact with Amazon S3 and other S3-compatible object storage systems like SeaweedFS and LocalStack. This tool provides a Model Context Protocol interface, allowing AI applications to perform data management and retrieval tasks directly on cloud storage. It supports various installation methods, including Go install, Docker images, Homebrew, and direct binary downloads, making it accessible across different development environments. MCP S3 aims to provide flexible and secure access to object storage for AI workloads.

What does MCP S3 connect to?

MCP S3 functions as a Model Context Protocol server, specifically designed to bridge AI assistants with Amazon S3 and other compatible object storage systems. This includes prominent services like AWS S3 itself, as well as alternative solutions such as SeaweedFS and LocalStack. Its core purpose is to provide AI applications with direct communication capabilities to these storage platforms, facilitating data access and manipulation within an AI-driven workflow. The program ensures AI assistants can interact with diverse object storage environments.

Core features and tools

MCP S3 exposes a set of callable tools for interacting with object storage. These include s3_list_buckets to discover storage containers, s3_list_objects to view contents, and s3_get_object for data retrieval. For object manipulation, it offers s3_put_object, s3_delete_object, and s3_copy_object. Additionally, s3_get_object_metadata allows inspection of object details. While functionality for presigned URLs exists, a dedicated s3_ prefixed tool name for this specific operation is not explicitly listed among the primary tools.

Who is it for?

MCP S3 targets AI assistants and developers who need flexible, secure access to object storage for their AI applications. It is compatible with AI clients such as Claude Code CLI, Claude Desktop, Cursor, Cline, and Amazon Q Developer. This solution is ideal for integrating AI capabilities directly with cloud storage for data discovery, analysis, and management tasks. Skip this if your AI application does not require direct programmatic interaction with S3 or S3-compatible object storage.

How to get started

The server authenticates using AWS credentials configured via environment variables. For client-server communication, it supports the stdio transport protocol, with credentials like AWS_ACCESS_KEY_ID set for standalone server operation.

Use cases

• AI assistants browsing S3 buckets and objects to discover and understand available data.
• AI assistants reading specific object content for tasks like analysis or retrieval-augmented generation.
• AI assistants performing data management operations such as writing, deleting, or copying objects (when explicitly enabled) for file organization or data migration.

MCP S3 by Txn2 offers a direct bridge between AI assistants and S3-compatible storage, providing essential object management tools. Its Go-based architecture and multi-platform distribution make it accessible for developers integrating AI with cloud data. The system supports various AI clients and allows for custom authentication when used as a library.