How to Use the Amazon Marketing Cloud MCP in AutoGen

Q: How do AutoGen agents collaborate on Amazon Marketing Cloud queries?

One agent drafts the SQL and calls createexecution, while another polls getexecutionstatus. They negotiate budget limits and query parameters before running any tool.

Q: Can an AutoGen agent delete an Amazon Marketing Cloud workflow?

Yes, a cleanup agent can call deleteworkflow after a supervisor agent confirms the query is no longer needed. This prevents clutter in your AMC account.

Q: How do AutoGen agents access Amazon Marketing Cloud data?

The agents use getexecutiondownloadurls to get secure links to the query results. They then download and parse the data to make strategic advertising decisions.

Let your AutoGen agents debate SQL optimization and execute Amazon Marketing Cloud queries autonomously via MCP.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Amazon Marketing Cloud MCP to AutoGen

Create your Vinkius account to connect Amazon Marketing Cloud to AutoGen 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 Marketing Cloud with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Coordinate multi-agent SQL execution via MCP Server

The `create_execution` tool allows your AutoGen database agent to run SQL queries while other agents review the results. A data analyst agent initiates the query, and a separate auditor agent monitors `get_execution_status` to ensure it completes. If the query takes too long or exceeds budget, the auditor agent triggers `delete_execution` to stop it.

Collaborative workflow management with AutoGen

Use `create_workflow` and `update_workflow` to let your AutoGen agents collaboratively build and refine your AMC query library. One agent drafts the SQL query based on marketing goals, while a security agent checks it against `get_workflow_details` to verify compliance. Once they agree, the execution agent deploys the workflow to keep your Amazon Marketing Cloud database clean and secure.

Automated data extraction and review

The `get_execution_download_urls` tool fetches the query output paths so your AutoGen agents can analyze the results. A retrieval agent pulls the CSV data, while an analyst agent extracts key metrics like conversion rates or click-throughs. If the workflow library gets cluttered, a maintenance agent uses `list_workflows` and `delete_workflow` to prune unused queries.

Setup guide

Set up Amazon Marketing Cloud MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Amazon Marketing Cloud tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Amazon Marketing Cloud_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Amazon Marketing Cloud data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Amazon Marketing Cloud_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Amazon Marketing Cloud data")
    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 Marketing Cloud. 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 Marketing Cloud 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 Marketing Cloud MCP in AutoGen

One agent drafts the SQL and calls `create_execution`, while another polls `get_execution_status`. They negotiate budget limits and query parameters before running any tool.

Yes, a cleanup agent can call `delete_workflow` after a supervisor agent confirms the query is no longer needed. This prevents clutter in your AMC account.

The agents use `get_execution_download_urls` to get secure links to the query results. They then download and parse the data to make strategic advertising decisions.

AutoGen logs all tool calls in its chat history. You can see exactly which agent initiated `create_execution` and how the other agents responded to the output.

Your SQL queries and execution status logs are processed entirely within your local AutoGen environment. The Vinkius MCP Server executes in a secure, ephemeral V8 sandbox, ensuring your marketing data remains strictly private.

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