How do I use aws-s3-connector-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@aws-s3-connector-mcp list objects in my S3 bucket" 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-connector-mcp

Q: Which integrations are available for this server?

Provides tools for connecting to AWS S3 buckets, listing objects, uploading files, and reading file contents, supporting both public and private buckets.

by sourav-spd

Overview Schema Related Servers Score Discussions

Python

Remote

AWS S3 Connector MCP Server

A production-ready Model Context Protocol (MCP) server for AWS S3 operations.

Provides 4 practical tools for connecting to S3, listing objects, uploading files, and reading file contents — supporting public buckets (no credentials) and private buckets (AWS credentials).

Supports three transport modes: stdio, SSE, and Streamable HTTP.

Folder Structure

aws-s3-connector-tool-updated/
|-- aws_s3_server.py       # Main server entry point
|-- Dockerfile
|-- LICENSE
|-- mcp.example.json
|-- pyproject.toml
|-- README.md
`-- tools/
    |-- __init__.py
    |-- s3_connector_tools.py
    `-- toolhandler.py

Related MCP server: S3 MCP Server

Available Tools (4)

Tool	Description
`connect_s3`	Connect to an S3 bucket via public URL or AWS credentials
`list_objects`	List all objects in the connected bucket with filenames and links
`upload_object`	Upload a file from a local path or internet URL to S3
`read_object`	Read file contents from S3 (CSV, JSON, Excel, PDF, Parquet, images, text)

Tools Reference

1. connect_s3

Connect to an S3 bucket. Call this first before using other tools.

Parameters:

Parameter	Required	Description
`bucket_url`	Yes (if no credentials)	Public S3 URL, e.g. `https://my-bucket.s3.amazonaws.com` or `s3://my-bucket`
`aws_access_key_id`	No	AWS access key (for private buckets)
`aws_secret_access_key`	No	AWS secret key (for private buckets)
`region`	No	AWS region (default: auto-detected or `us-east-1`)

Example — public bucket:

{
  "bucket_url": "https://my-public-bucket.s3.amazonaws.com"
}

Example — private bucket:

{
  "aws_access_key_id": "<access-key>",
  "aws_secret_access_key": "<secret-key>",
  "bucket_url": "s3://my-private-bucket",
  "region": "us-east-1"
}

Returns:

{
  "status": "connected",
  "bucket": "my-bucket",
  "region": "us-east-1",
  "mode": "public"
}

2. list_objects

List all objects in the connected S3 bucket with filenames and presigned/public links.

Parameters: none (uses connection from connect_s3)

Example:

{}

Returns:

{
  "status": "success",
  "bucket": "my-bucket",
  "count": 3,
  "objects": [
    {
      "key": "data/report.csv",
      "size": 4096,
      "last_modified": "2026-06-01T10:00:00Z",
      "url": "https://my-bucket.s3.amazonaws.com/data/report.csv?..."
    }
  ]
}

3. upload_object

Upload a file to the connected S3 bucket from a local path or a URL.

Parameters:

Parameter	Required	Description
`key`	Yes	Destination S3 key (path in bucket), e.g. `uploads/file.csv`
`local_path`	No*	Absolute local file path
`source_url`	No*	Internet URL to download and upload

*One of local_path or source_url is required.

Example — local file:

{
  "key": "uploads/report.csv",
  "local_path": "C:/Users/me/Downloads/report.csv"
}

Example — from URL:

{
  "key": "uploads/data.json",
  "source_url": "https://example.com/data.json"
}

Returns:

{
  "status": "success",
  "key": "uploads/report.csv",
  "bucket": "my-bucket",
  "message": "Uploaded successfully"
}

4. read_object

Read and return the contents of a file stored in S3. Supports multiple file formats.

Parameters:

Parameter	Required	Description
`key`	Yes	S3 object key to read

Supported formats:

Format	Extensions	Output
Text / CSV / JSON	`.txt`, `.csv`, `.json`, `.md`, `.log`, `.xml`, `.html`, `.yaml`, `.yml`	Raw text
Excel	`.xlsx`, `.xls`	JSON rows per sheet
Parquet	`.parquet`	JSON rows
PDF	`.pdf`	Extracted text
Images	`.png`, `.jpg`, `.jpeg`, `.gif`, `.webp`	Base64-encoded data URL
Other	any	Base64-encoded content

Example:

{
  "key": "data/report.csv"
}

Returns:

{
  "status": "success",
  "key": "data/report.csv",
  "format": "text",
  "content": "id,name,value\n1,Alice,100\n2,Bob,200\n"
}

Prerequisites

Python 3.10+
AWS credentials (only for private buckets)

Installation

# From the workspace root (where .venv lives)
.venv\Scripts\activate          # Windows
# source .venv/bin/activate     # macOS / Linux

cd aws-s3-connector-tool-updated
pip install -e .

Run

stdio (default — for MCP desktop clients like Claude Desktop)

aws-s3-connector-mcp --mode stdio

SSE

aws-s3-connector-mcp --mode sse --host 0.0.0.0 --port 8000

Endpoints:

GET /sse
POST /messages/
GET /health

Streamable HTTP

aws-s3-connector-mcp --mode streamable-http --host 0.0.0.0 --port 8000

Endpoints:

POST /mcp
GET /health
GET /

Environment variables (alternative to CLI flags)

Variable	Default	Description
`TRANSPORT_TYPE`	`stdio`	`stdio` / `sse` / `streamable-http`
`APP_HOST`	`0.0.0.0`	Bind host
`APP_PORT`	`8000`	Bind port

Docker

# Build
docker build -t aws-s3-connector-mcp .

# Run (streamable-http, port 8000)
docker run -p 8000:8000 \
  -e AWS_ACCESS_KEY_ID=<your-key> \
  -e AWS_SECRET_ACCESS_KEY=<your-secret> \
  aws-s3-connector-mcp

MCP Client Configuration

See mcp.example.json for a ready-to-use client config snippet.

stdio (Claude Desktop / Cursor):

{
  "mcpServers": {
    "aws-s3-connector": {
      "command": "aws-s3-connector-mcp",
      "args": ["--mode", "stdio"],
      "env": {
        "AWS_ACCESS_KEY_ID": "<your-access-key>",
        "AWS_SECRET_ACCESS_KEY": "<your-secret-key>",
        "AWS_REGION": "us-east-1"
      }
    }
  }
}

Streamable HTTP (MCP Inspector / MCPmon):

http://localhost:8000/mcp

Architecture

MCP Client (Claude / Cursor / MCP Inspector)
    |
    | JSON-RPC 2.0
    v
Transport Layer (stdio | SSE | Streamable HTTP)   ← aws_s3_server.py
    |
    v
ToolHandler Registry (4 tools)
    |
    v
S3 Tool Handlers                                  ← tools/s3_connector_tools.py
    |
    v
boto3  ──►  AWS S3 API

Troubleshooting

NoCredentialsError — Pass credentials via connect_s3 or set AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY env vars.

NoSuchBucket — Verify the bucket name and region in connect_s3.

connect_s3 not called — Always call connect_s3 before list_objects, upload_object, or read_object.

Port already in use — Change APP_PORT env var or use --port flag.

License

MIT License — see LICENSE for details.

Install Server

license - permissive license

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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