The Sample S3 MCP Server provides a targeted way to fetch and expose AWS S3 bucket data to a Language Model Context Protocol. It exposes S3 data via Resources, which are akin to GET endpoints used to preload information into an LLM's context. The current implementation focuses on PDF documents, pulling from buckets and capping the number of accessible objects at 1,000 to balance performance and cost. The server includes tools that map to common S3 operations: ListBuckets lists all buckets owned by the authenticated user; ListObjectsV2 returns a subset of objects in a bucket (up to 1,000 per request); and GetObject retrieves a specific object by key, supporting both virtual-hosted-style and path-style requests. Configuration instructions describe how to set up AWS credentials with proper read/write permissions, and usage details show how to run the server within Claude Desktop or published server configurations. The development and debugging sections outline how to build, publish to PyPI, and debug using the MCP Inspector. The license is MIT-0.