What are the runtime dependencies?
Python 3.8 or later, plus packages `aioboto3`, `mcp[cli]`, and `python-dotenv`.
@abdullahsayyad
Basic information
A tool written in complete python following the MCP(model context protocol). LLM can leverage this tool to work with aws S3 buckets
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"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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.
Python 3.8 or later, plus packages `aioboto3`, `mcp[cli]`, and `python-dotenv`.
Set the `S3_BUCKETS` environment variable to a comma-separated list of bucket names (e.g., `bucket1,bucket2`). Only those buckets will be accessible.
Use the following JSON in your MCP configuration: `{ "mcpServers": { "AWS-S3-AccessTool": { "command": "python", "args": ["C:\\your-absolute-path-to-the-file\\main.py"] } } }`
It is open-source under the MIT License.
Yes, the README mentions integration via Docker, but no specific Docker instructions are provided.
MCP Workspace Server: A secure Model Context Protocol server providing file, git, and GitHub tools for AI assistants within a sandboxed project directory.

Model Context Protocol Servers
A lightweight MCP server for processing, editing, and interacting with PDF, Word, Excel, and CSV documents.

Upload once. Find, use and share across your AI workflows. drop.media is one media library for you and every AI agent you use: files added from Claude, ChatGPT, Cursor, the terminal or the web can be found, reused and sh
MCP server to extract contents from a PDF file
Comments