aws-s3-universal-mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@aws-s3-universal-mcp-serverlist all buckets in my account"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Aws-s3 Universal MCP Server
This repository contains an implementation of an Aws-s3 Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Aws-s3's tools and services through a unified API.
The server is built using the Universal MCP framework.
This implementation follows the MCP specification, ensuring compatibility with other MCP-compliant services and tools.
Usage
You can start using Aws-s3 directly from agentr.dev. Visit agentr.dev/apps and enable Aws-s3.
If you have not used universal mcp before follow the setup instructions at agentr.dev/quickstart
Related MCP server: S3 MCP Server
Available Tools
The full list of available tools is at ./src/universal_mcp_aws_s3/README.md
Local Development
š Prerequisites
Ensure you have the following before you begin:
Python 3.11+ (recommended)
uv (install globally with
pip install uv)
š ļø Setup Instructions
Follow the steps below to set up your development environment:
Sync Project Dependencies
uv syncThis installs all dependencies from
pyproject.tomlinto a local virtual environment (.venv).Activate the Virtual Environment
For Linux/macOS:
source .venv/bin/activateFor Windows (PowerShell):
.venv\Scripts\ActivateStart the MCP Inspector
mcp dev src/universal_mcp_aws_s3/server.pyThis will start the MCP inspector. Make note of the address and port shown in the console output.
Install the Application
mcp install src/universal_mcp_aws_s3/server.py
š Project Structure
.
āāā src/
ā āāā universal_mcp_aws_s3/
ā āāā __init__.py # Package initializer
ā āāā server.py # Server entry point
ā āāā app.py # Application tools
ā āāā README.md # List of application tools
āāā tests/ # Test suite
āāā .env # Environment variables for local development
āāā pyproject.toml # Project configuration
āāā README.md # This fileš License
This project is licensed under the MIT License.
Generated with MCP CLI ā Happy coding! š
This server cannot be deployed
Maintenance
Related MCP Connectors
Unified gateway exposing 150+ tools across all NexGenData MCP servers via one endpoint.
Governed MCP gateway: one endpoint for your tools, with credential custody and audit log.
Unified MCP Server is a remote MCP connector for AI agents and vertical AI products that provides access to 22,000+ authorized SaaS tools across 400+ integrations and 24 categories directly inside LLMs (Claude, GPT, Gemini, Cohere). Tools operate only on explicitly authorized customer connections, enabling agents to safely read and write against live third-party systems.
Related MCP Servers
- FlicenseBqualityDmaintenanceAn MCP server that provides tools for interacting with AWS S3 buckets, enabling direct access to S3 operations through the Model Context Protocol.1-
- AlicenseNot gradedqualityFmaintenanceEnables interaction with AWS S3 through MCP, supporting bucket and object management, lifecycle configurations, tagging, policies, CORS settings, presigned URLs, and file uploads/downloads.3MIT
- AlicenseAqualityCmaintenanceEnables MCP clients to connect to AWS S3 buckets, list, upload, and read objects in various formats, supporting public and private buckets with multiple transport modes.4MIT
- AlicenseNot gradedqualityAmaintenanceProvides MCP tools for AWS S3 and S3-compatible storage, enabling file upload, download, listing, deletion, and temporary remote file staging via natural language.BSD 3-Clause