How do I get my AWS Access Key and Secret Key?

Log in to the AWS Management Console, navigate to IAM (Identity and Access Management), and create a user with programmatic access. Ensure this user has S3 permissions (e.g., `AmazonS3FullAccess`). You will receive an Access Key ID and a Secret Access Key.

Can I upload large files using this integration?

The `put_object` tool handles standard REST uploads and is best suited for small to medium-sized files or JSON data. For very large files, standard AWS tools utilizing Multipart Uploads are recommended.

How do I ensure my buckets are secure?

You can use the `get_bucket_policy` and `get_bucket_acl` tools to audit the current access controls applied to any of your buckets directly from the chat.

Amazon S3 MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Amazon S3
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Amazon S3 through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "amazon-s3": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Amazon S3, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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 MCP Server

Connect your Amazon S3 environment to your AI agent to unlock professional cloud storage orchestration. From creating and auditing buckets to managing individual objects and their metadata, your agent handles your AWS data storage through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Amazon S3 through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Bucket Orchestration — List your S3 buckets, create new ones, and retrieve their location or policy configurations
Object Management — List objects within a specific bucket, including their size and last modified timestamps
Data Ingestion — Upload objects directly to S3 or delete unwanted files to maintain your storage hygiene
Metadata Auditing — Retrieve technical metadata (headers, content type, size) for specific objects without downloading them
Security Oversight — Audit bucket ACLs and policies to ensure your cloud storage meets compliance requirements

The Amazon S3 MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Amazon S3 to LangChain via MCP

Follow these steps to integrate the Amazon S3 MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Amazon S3 via MCP

Why Use LangChain with the Amazon S3 MCP Server

LangChain provides unique advantages when paired with Amazon S3 through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Amazon S3 MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Amazon S3 queries for multi-turn workflows

Amazon S3 + LangChain Use Cases

Practical scenarios where LangChain combined with the Amazon S3 MCP Server delivers measurable value.

RAG with live data: combine Amazon S3 tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Amazon S3, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Amazon S3 tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Amazon S3 tool call, measure latency, and optimize your agent's performance

Amazon S3 MCP Tools for LangChain (10)

These 10 tools become available when you connect Amazon S3 to LangChain via MCP:

create_bucket

Create an S3 bucket

delete_bucket

Delete an S3 bucket

delete_object

Delete an object

get_bucket_acl

Get bucket ACL

get_bucket_policy

Get bucket policy

get_object_data

Get object content

get_object_metadata

Get object metadata

list_buckets

List S3 buckets

list_objects

Can be filtered by prefix. List objects in bucket

put_object

Upload an object

Example Prompts for Amazon S3 in LangChain

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

"List all S3 buckets in my account."

"Show the top 10 objects in bucket 'data-lake-raw' starting with prefix '2026/03/'."

"Get the bucket policy for 'website-images-eu'."

Troubleshooting Amazon S3 MCP Server with LangChain

Common issues when connecting Amazon S3 to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Amazon S3 + LangChain FAQ

Common questions about integrating Amazon S3 MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.