This MCP enables LLMs to interact with AWS S3, providing functions to list buckets, list objects, and retrieve objects securely and efficiently.
Added on:
Created by:
Apr 13 2025
This MCP enables LLMs to interact with AWS S3, providing functions to list buckets, list objects, and retrieve objects securely and efficiently.
Added on:
Created by:
Apr 13 2025
Yuichi Kojima
Featured
What is AWS S3 MCP?
The AWS S3 MCP (Model Context Protocol) server facilitates seamless interaction between Large Language Models and AWS S3 storage. It offers functionalities such as listing available S3 buckets, enumerating objects within specific buckets, and retrieving object contents for analysis or processing. Built with TypeScript and the MCP SDK, it ensures a standardized and secure method for integrating S3 operations into AI workflows. Users can configure access via environment variables or Docker, and use tools like list-buckets, list-objects, and get-object to manage S3 resources programmatically. The server is suitable for developers, data scientists, and AI platform integrators aiming to automate storage management tasks within their AI applications.
Who will use AWS S3 MCP?
- Developers
- Data Scientists
- AI Platform Integrators
How to use the AWS S3 MCP?
- Step1: Configure AWS credentials and environment variables
- Step2: Install the MCP server via npm, Docker, or build from source
- Step3: Run the server locally or as a Docker container
- Step4: Connect the MCP server to your LLM or AI platform
- Step5: Use available tools like list-buckets, list-objects, and get-object for S3 interactions
AWS S3 MCP's Core Features & Benefits
The Core Features
- list-buckets
- list-objects
- get-object
The Benefits
- Secure and standardized AWS S3 access for LLMs
- Automates S3 bucket and object management
- Supports configuration via environment variables or Docker
- Compatible with AI workflows for data retrieval and analysis
AWS S3 MCP's Main Use Cases & Applications
- Automated S3 bucket and object management within AI applications
- Retrieving and summarizing documents stored in S3 for NLP tasks
- Integrating S3 data management into AI-powered data analysis pipelines
FAQs of AWS S3 MCP
Developer
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Cloud Platforms
A Spring-based chatbot for Cloud Foundry that integrates with AI services, MCP, and memGPT for advanced capabilities.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
Automates MCP server creation for AWS services using boto3, simplifying server setup for development.
Demo project showcasing MCP protocol integration with Azure OpenAI for seamless AI application interactions.
A serverless MCP hosted in AWS Lambda that interacts with AWS Bedrock for AI model processing via API Gateway.
A dynamic MCP server facilitating interaction with Etherscan's API for blockchain data retrieval.
A server-client MCP facilitating communication and data exchange between AI services and storage systems.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
Enables interaction with SharePoint Online via REST API, supporting site, list, and user management functions.
A comprehensive suite of containers for efficient microservices deployment and management.
Cloud Storage
A server enabling AI models to securely list and download files from AWS S3 buckets.
A Python-based MCP client for Google Drive that enables natural language file management and retrieval.
Integrates Google Drive with file listing, reading, and search functionalities for various file types.
A server enabling AI clients to access Qiniu Cloud storage and multimedia services via MCP protocol.
A multi-cloud storage service supporting file uploads, presigned URLs, and custom domains for various cloud providers.
A self-sovereign data server enabling decentralized AI application storage using IPFS and CIDs.
Implements management functions for OceanBase clusters, tenants, and backup policies via MCP protocol.
A server for managing MCP hooks to integrate with Arweave Storage SDK, enabling custom data handling.
MCP server integrating Spring Boot, Spring AI, and Cloudflare R2 for object storage management
Enables LLM agents to interact with AWS S3 for file management including listing, uploading, reading, and deleting files.