Sample S3 Model Context Protocol Server
Description
# Sample S3 Model Context Protocol Server 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…
About
# Sample S3 Model Context Protocol Server 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…
Details
- Author
- aws-samples
- GitHub stars
- 78
- Downloads
- 588
- Categories
- File Management, Other
Jump to
- Exposes AWS S3 data through MCP Resources (PDF documents only, limit 1000 objects)
- Provides ListBuckets tool to list all buckets owned by the authenticated sender
- Provides ListObjectsV2 tool to list up to 1000 objects in a bucket
- Provides GetObject tool to retrieve an object by its full key name
- Supports virtual-hosted-style and path-style requests for GetObject
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Sample S3 Model Context Protocol ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Obtain AWS credentials with appropriate S3 permissions, then configure the server in Claude Desktop's config file using either the development command (uv) or the published server command (uvx). The server provides tools and resources for interacting with S3 buckets and objects.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"sample s3 model context protocol server": {
"sample-mcp-server-s3": {
"command": "uv",
"args": [
"sync"
]
}
}
}
}McpServers
{
"sample-mcp-server-s3": {
"command": "uv",
"args": [
"sync"
]
}
}Sample S3 Model Context Protocol Server
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 supportedConfiguration
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
<details>
<summary>Development/Unpublished Servers Configuration</summary>
{
"mcpServers": {
"s3-mcp-server": {
"command": "uv",
"args": [
"--directory",
"/Users/user/generative_ai/model_context_protocol/s3-mcp-server",
"run",
"s3-mcp-server"
]
}
}
}
</details>
<details>
<summary>Published Servers Configuration</summary>
{
"mcpServers": {
"s3-mcp-server": {
"command": "uvx",
"args": [
"s3-mcp-server"
]
}
}
}
Development
Building and Publishing
To prepare the package for distribution:
1. Sync dependencies and update lockfile:
uv sync
2. Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
3. Publish to PyPI:
uv publish
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:
npx @modelcontextprotocol/inspector uv --directory /Users/user/generative_ai/model_context_protocol/s3-mcp-server run s3-mcp-server
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Security
See CONTRIBUTING for more information.
License
This library is licensed under the MIT-0 License. See the LICENSE file.
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