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aws-s3-connector-mcp

by sourav-spd
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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: AWS 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

s3_url

Yes (if no credentials)

Public S3 URL, e.g. https://my-bucket.s3.amazonaws.com or s3://my-bucket

bucket_url

Alias

Alias of s3_url (supported for compatibility)

aws_access_key_id

No

AWS access key (for private buckets)

aws_secret_access_key

No

AWS secret key (for private buckets)

region_name

No

AWS region (default: auto-detected or us-east-1)

region

Alias

Alias of region_name (supported for compatibility)

Example — public bucket:

{
  "s3_url": "https://my-public-bucket.s3.amazonaws.com"
}

Example — private bucket:

{
  "aws_access_key_id": "<access-key>",
  "aws_secret_access_key": "<secret-key>",
  "s3_url": "s3://my-private-bucket",
  "region_name": "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

object_key

Yes

Destination S3 key (path in bucket), e.g. uploads/file.csv

key

Alias

Alias of object_key (supported for compatibility)

local_file_path

No*

Absolute local file path

local_path

Alias

Alias of local_file_path (supported for compatibility)

source_url

No*

Internet URL to download and upload

*One of local_path or source_url is required.

Example — local file:

{
  "object_key": "uploads/report.csv",
  "local_file_path": "C:/Users/me/Downloads/report.csv"
}

Example — from URL:

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

Returns:

{
  "status": "success",
  "object_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

object_key

Yes

S3 object key to read

key

Alias

Alias of object_key (supported for compatibility)

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:

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

Returns:

{
  "status": "success",
  "object_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 (also supports /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": "AKIA...",
        "AWS_SECRET_ACCESS_KEY": "your-secret-key",
        "AWS_REGION": "ap-south-1",
        "S3_BUCKET": "customer-kyc-demo"
      }
    }
  }
}

With this env format, you can run connect_s3 with empty arguments:

{}

Streamable HTTP (MCP Inspector / MCPmon):

http://localhost:8000/mcp

For SSE in MCP Inspector, use:

http://127.0.0.1:8000/sse

Avoid 0.0.0.0 in the inspector URL.

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.

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