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Amazon S3 Bucket MCP Server for Google ADKGive Google ADK instant access to 7 tools to Delete Object, Get Bucket Acl, Get Bucket Policy, and more

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Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Amazon S3 Bucket as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Ask AI about this MCP Server for Google ADK

The Amazon S3 Bucket MCP Server for Google ADK is a standout in the Industry Titans category — giving your AI agent 7 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="amazon_s3_bucket_agent",
    instruction=(
        "You help users interact with Amazon S3 Bucket "
        "using 7 available tools."
    ),
    tools=[mcp_tools],
)
Amazon S3 Bucket
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Amazon S3 Bucket MCP Server

Grant your AI agent precise, scoped access to a single Amazon S3 bucket — no more, no less. Unlike full S3 access, this integration enforces the principle of least privilege: your agent can read, write, and manage objects exclusively within one pre-configured bucket.

Google ADK natively supports Amazon S3 Bucket as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 7 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

  • Browse Objects — List and navigate files within the bucket using prefix and delimiter filters
  • Read Data — Retrieve object contents or inspect metadata (headers, content type, size) without downloading
  • Write Data — Upload string or JSON content as objects directly into the bucket
  • Clean Up — Delete specific objects to maintain storage hygiene
  • Audit Security — Inspect the bucket's access policy and ACL to ensure compliance

Why single-bucket?

AI agents should follow the principle of least privilege. Granting full S3 access to an autonomous agent creates unnecessary blast radius. This server confines the agent to a single bucket, which means:

  • No accidental bucket creation or deletion

  • No cross-bucket data exposure

  • Clearer audit trail for compliance

  • Safer agent-to-agent delegation


The Amazon S3 Bucket MCP Server exposes 7 tools through the Vinkius. Connect it to Google ADK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 7 Amazon S3 Bucket tools available for Google ADK

When Google ADK connects to Amazon S3 Bucket through Vinkius, your AI agent gets direct access to every tool listed below — spanning object-storage, aws, data-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

delete

Delete object on Amazon S3 Bucket

Delete an object

get

Get bucket acl on Amazon S3 Bucket

Get bucket ACL

get

Get bucket policy on Amazon S3 Bucket

Get bucket policy

get

Get object data on Amazon S3 Bucket

Get object content

get

Get object metadata on Amazon S3 Bucket

Get object metadata

list

List objects on Amazon S3 Bucket

Can be filtered by prefix and delimiter. List objects in the bucket

put

Put object on Amazon S3 Bucket

Upload an object

Connect Amazon S3 Bucket to Google ADK via MCP

Follow these steps to wire Amazon S3 Bucket into Google ADK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install Google ADK

Run pip install google-adk
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Create the agent

Save the code above and integrate into your ADK workflow
04

Explore tools

The agent will discover 7 tools from Amazon S3 Bucket via MCP

Why Use Google ADK with the Amazon S3 Bucket MCP Server

Google ADK provides unique advantages when paired with Amazon S3 Bucket through the Model Context Protocol.

01

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

02

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Amazon S3 Bucket

03

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

04

Seamless integration with Google Cloud services means you can combine Amazon S3 Bucket tools with BigQuery, Vertex AI, and Cloud Functions

Amazon S3 Bucket + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Amazon S3 Bucket MCP Server delivers measurable value.

01

Enterprise data agents: ADK agents query Amazon S3 Bucket and cross-reference results with internal databases for comprehensive analysis

02

Multi-modal workflows: combine Amazon S3 Bucket tool responses with Gemini's vision and language capabilities in a single agent

03

Automated compliance checks: schedule ADK agents to query Amazon S3 Bucket regularly and flag policy violations or configuration drift

04

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Amazon S3 Bucket

Example Prompts for Amazon S3 Bucket in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Amazon S3 Bucket immediately.

01

"List all files in this bucket."

02

"Upload this JSON config to 'settings/app-config.json'."

03

"Check the access policy on this bucket."

Troubleshooting Amazon S3 Bucket MCP Server with Google ADK

Common issues when connecting Amazon S3 Bucket to Google ADK through Vinkius, and how to resolve them.

01

McpToolset not found

Update: pip install --upgrade google-adk

Amazon S3 Bucket + Google ADK FAQ

Common questions about integrating Amazon S3 Bucket MCP Server with Google ADK.

01

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
02

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
03

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.

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