Server Overview

mcp-s3 runs as a standalone MCP server that provides S3 operations to AI assistants through the Model Context Protocol.

How It Works

1. MCP Transport: The server communicates via stdio, making it compatible with any MCP client
2. Tool Registration: S3 operations are exposed as MCP tools that AI assistants can call
3. AWS SDK: Uses the official AWS SDK v2 for reliable S3 operations
4. Extensions: Built-in middleware provides logging, metrics, and access control

Architecture

flowchart TB
    subgraph AI["AI Assistant (Claude, etc.)"]
    end

    subgraph Server["mcp-s3 Server"]
        MCP["MCP Server Layer<br/>(Tool Registration, Handlers)"]
        Toolkit["Toolkit Layer<br/>(Middleware, Interceptors, Transformers)"]
        Client["Client Layer<br/>(AWS SDK v2 Wrapper)"]

        MCP --> Toolkit
        Toolkit --> Client
    end

    subgraph S3["S3 / S3-Compatible Service"]
        Storage["AWS S3, SeaweedFS, LocalStack, etc."]
    end

    AI -->|"MCP Protocol (stdio)"| MCP
    Client -->|"HTTPS"| Storage

Safety Features

mcp-s3 is designed with safety as a priority:

• Read-Only Default: Write operations (put, delete, copy) are blocked by default
• Size Limits: Maximum object sizes for get (10MB) and put (100MB) operations
• No Credential Exposure: Credentials are never exposed through MCP tools

Use Cases

• Data Exploration: Browse and read files in S3 buckets
• Content Analysis: Retrieve documents, logs, or data files for AI analysis
• File Management: Upload, copy, and organize files (when write is enabled)
• URL Generation: Create temporary presigned URLs for sharing