How to Use the Amazon Selling Partner MCP in AutoGen
Let AutoGen agents debate and coordinate Amazon Selling Partner inventory and order decisions.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Amazon Selling Partner MCP to AutoGen
Create your Vinkius account to connect Amazon Selling Partner 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.
Run AutoGen agent debates on Amazon Selling Partner data
The `list_orders` tool provides the raw transactional data that your AutoGen agents need to collaborate on Amazon order fulfillment. One AutoGen agent can fetch the Amazon orders while a separate verification agent analyzes the items using `get_order_items` to flag high-risk purchases. This MCP Server integration enables consensus-driven Amazon e-commerce operations inside AutoGen. Your AutoGen agents discuss and resolve Amazon order discrepancies in a structured conversation before taking any action.
Coordinate Amazon inventory audits using AutoGen agents
The `list_fba_inventory` tool lets your AutoGen supply chain agent monitor Amazon stock levels in real time using the MCP tool. If Amazon inventory drops, this AutoGen agent can debate with a purchasing agent about whether to trigger an Amazon restock report using `create_report`. This cooperative AutoGen approach ensures you don't over-order on Amazon. The AutoGen agents deliberate, weigh historical Amazon velocity against current stock, and agree on the best course of action.
Reconcile Amazon financial events in AutoGen conversations
The `list_financial_events` tool feeds Amazon financial data directly into a multi-agent AutoGen reconciliation workflow. An AutoGen billing agent can pull the Amazon events, while an audit agent cross-references them against your active catalog using `list_product_types`. By separating these Amazon financial concerns into specialized AutoGen agents, you get cleaner audits. They argue over Amazon discrepancies until they reach a consensus on your net margins.
Set up Amazon Selling Partner 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Amazon Selling Partner tools and returns structured results.
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 Selling Partner_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Amazon Selling Partner data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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 Selling Partner_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Amazon Selling Partner data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amazon Selling Partner. 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.
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Common questions about Amazon Selling Partner MCP in AutoGen
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