An MCP server that allows natural language interaction with AWS S3 through an LLM, using Spring Boot IA.
{
"mcpServers": {
"s3-toolbox-mcp-server": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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An MCP server that allows natural language interaction with AWS S3 through an LLM, using Spring Boot IA.
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
MIT. View license →
Is it maintained?
Last commit 318 days ago. 1 stars.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
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A Model Context Protocol (MCP) server that makes interacting with AWS S3 buckets a breeze. Built using Spring AI MCP, it uses STDIO transport for seamless communication, making it perfect for integration with modern development tools like Cursor IDE and AI agents. This server bridges the gap between your development environment and S3 operations, enabling natural language interactions for both automation tasks and interactive development.
The S3 Toolbox MCP Server exposes core AWS S3 operations through a simple MCP interface, leveraging Spring AI's Model Context Protocol implementation. This means AI agents can naturally interact with your S3 buckets using plain language, while maintaining precise control over the operations.
The server provides the following S3 operations:
list_s3_buckets)

list_s3_files)
bucketName: Target bucket nameprefix: Optional folder path filter
put_s3_object)
bucketName: Target bucket namefileName: Name for the file in S3contentType: MIME type (e.g., 'application/pdf', 'image/png')prefix: Optional path prefix/folder inside the bucketbase64Content: File content encoded in Base64 format
get_s3_object)
bucketName: Source bucketkey: File path in S3
get_s3_object_metadata)
bucketName: Target bucketkey: File path in S3
delete_s3_object)
bucketName: Target bucketkey: File to delete
Clone the repo:
Build the JAR:
Using Maven Wrapper (recommended):
# For Windows
./mvnw.cmd clean package
# For Linux/Mac
./mvnw clean package
Or if you have Maven installed:
mvn clean package
The JAR will be created in the target directory as s3-toolbox-mcp-server-1.0.0.jar
mcp-config.json):{
"mcpServers": {
"s3-toolbox-mcp-server": {
"command": "java",
"args": [
"-jar",
"path/to/s3-toolbox-mcp-server-1.0.0.jar"
],
"env": {
"AWS_ACCESS_KEY_ID": "your-access-key",
"AWS_SECRET_ACCESS_KEY": "your-secret-key",
"AWS_REGION": "us-east-1"
}
}
}
}
Replace the following:
path/to/s3-toolbox-mcp-server-1.0.0.jar: Full path to the built JAR file (e.g., C:\Users\YourUser\s3-toolbox-mcp-server\target\s3-toolbox-mcp-server-1.0.0.jar)your-access-key: Your AWS access key IDyour-secret-key: Your AWS secret access keyus-east-1: Your desired AWS regionThe server uses STDIO transport for communication with MCP clients, making it easy to integrate with any MCP-compatible client. Once configured, you can use the client to interact with your S3 buckets through natural language commands.
I wanted to bridge the gap between AI agents and S3 operations. While AWS prov