aws-samples/sample-mcp-server-s3

An MCP server implementation for retrieving data such as PDF's from S3.
Features
Resources
Expose AWS S3 Data through **Resources**. (think of these sort of like GET endpoints; they are used to load information into the LLM's context). Currently only **PDF** documents supported and limited to **1000** objects.
Tools
- **ListBuckets**
- Returns a list of all buckets owned by the authenticated sender of the request
- **ListObjectsV2**
- Returns some or all (up to 1,000) of the objects in a bucket with each request
- **GetObject**
- Retrieves an object from Amazon S3. In the GetObject request, specify the full key name for the object. General purpose buckets - Both the virtual-hosted-style requests and the path-style requests are supported
Configuration
Setting up AWS Credentials
1. Obtain AWS access key ID, secret access key, and region from the AWS Management Console.
2. Ensure these credentials have appropriate permissions for AWS S3.
Usage with Claude Desktop
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
Published Servers Configuration
Development
Building and Publishing
To prepare the package for distribution:
1. Sync dependencies and update lockfile:
2. Build package distributions:
This will create source and wheel distributions in the dist/ directory.
3. Publish to PyPI:
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: --token or UV_PUBLISH_TOKEN
- Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.