How to Use the Amazon SQS Queue MCP in LangChain

Q: Can my LangChain agent process multiple messages at once?

Yes. The receivemessages tool includes a maxnumberofmessages parameter. Your agent can request up to 10 messages at a time and loop through them in its logic.

Build event-driven agents in LangChain that react to your Amazon SQS messages.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Amazon SQS Queue MCP to LangChain

Create your Vinkius account to connect Amazon SQS Queue to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Amazon SQS Queue with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Process Queued Jobs, Step-by-Step

Your agent uses the `receive_messages` tool to pull jobs from a queue. Then, you can have it use other LangChain tools to process that data—look up a user, enrich a record, or call a different API. It’s a simple, reliable way to build background workers. Once the job's done, the agent calls `delete_message` to take it off the queue. This pattern creates traceable workflows for handling asynchronous tasks right inside your agentic chain. You'll see every step in LangSmith.

Create Asynchronous Chains

Don't block your main application waiting for a long task to finish. Use the `send_message` tool to push a job to an SQS queue. A separate worker agent, running on its own schedule, can then pick it up when it's ready. This lets you build complex, multi-part systems where different agents communicate through a central message bus. It's a classic pattern for building durable software, now available to your AI agent.

Your LangChain SQS Toolkit

This MCP Server gives your agent three direct actions: `send_message`, `receive_messages`, and `delete_message`. You aren't just connecting to AWS; you're giving your agent the basic building blocks to interact with a queue as part of a larger reasoning loop. The server is a solid piece of infrastructure for any event-driven automation. Because every tool call is a link in a chain, you get a clear view of how your agent decides to act on incoming messages.

Setup guide

Set up Amazon SQS Queue MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Amazon SQS Queue tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "amazon-sqs-queue-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Amazon SQS Queue transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amazon SQS Queue. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Amazon SQS Queue now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Amazon SQS Queue MCP in LangChain

You connect this MCP Server to the MultiServerMCPClient and get the tools. Then, you pass those tools to your agent. Your agent can then decide to call `send_message`, `receive_messages`, or `delete_message` as part of a chain.

Yes. The `receive_messages` tool includes a `max_number_of_messages` parameter. Your agent can request up to 10 messages at a time and loop through them in its logic.

The message remains in the queue and becomes visible again after the visibility timeout expires. This allows another agent instance or a later run to retry processing it, preventing data loss.

Yes, it's perfect for that. This MCP server does one thing: it sends, receives, and deletes SQS messages. There's no extra complexity, which makes it a dependable tool for your chains.

Your SQS message content is only ever in memory within the Vinkius sandbox while your agent is processing it. The server is ephemeral—it spins up for the request and shuts down right after. Vinkius handles the AWS authentication, so your keys are never exposed.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript