AWS S3 AccessTool MCP Server

@abdullahsayyad

Basic information

About AWS S3 AccessTool MCP Server

A tool written in complete python following the MCP(model context protocol). LLM can leverage this tool to work with aws S3 buckets

#aws-s3#s3-access-tool#cloud-storage

AWS S3 AccessTool MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "AWS-S3-AccessTool": {
      "command": "python",
      "args": [
        "C:your-absolute-path-to-the-file\\main.py"
      ]
    }
  }
}

AWS S3 AccessTool MCP Server tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is AWS S3 AccessTool?

AWS S3 AccessTool is an MCP server utility that enables LLMs to interact with AWS S3 storage. It can list available buckets, retrieve stored objects, filter for CSV files, and read CSV content, with built-in async support via aioboto3. Developers can integrate it locally or via Docker, and it supports environment-based bucket selection.

How to use AWS S3 AccessTool?

Install dependencies: pip install aioboto3 mcp[cli] python-dotenv. Set environment variables AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, and optionally S3_BUCKETS to restrict access. Then configure your MCP client (e.g., Cursor.ai) with the command python and the absolute path to main.py.

Key features of AWS S3 AccessTool

List available S3 buckets
Fetch objects from specific or all buckets
Filter and retrieve only CSV files
Read the content of a CSV file from S3

Use cases of AWS S3 AccessTool

Automate listing of all S3 buckets in an account
Retrieve specific objects from one or multiple buckets
Filter and download CSV files for data analysis
Integrate CSV content reading into LLM workflows

Frequently asked questions

What are the runtime dependencies?

Python 3.8 or later, plus packages `aioboto3`, `mcp[cli]`, and `python-dotenv`.

How do I restrict access to specific buckets?

Set the `S3_BUCKETS` environment variable to a comma-separated list of bucket names (e.g., `bucket1,bucket2`). Only those buckets will be accessible.

How do I configure this tool for Cursor.ai?

Use the following JSON in your MCP configuration: `{ "mcpServers": { "AWS-S3-AccessTool": { "command": "python", "args": ["C:\\your-absolute-path-to-the-file\\main.py"] } } }`

What license is the project under?

It is open-source under the MIT License.

Does the tool support Docker deployment?

Yes, the README mentions integration via Docker, but no specific Docker instructions are provided.

Comments

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