How to Use the Jumpseller MCP in AutoGen
Let your AutoGen agents debate and coordinate store tasks using live Jumpseller product and order data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Jumpseller MCP to AutoGen
Create your Vinkius account to connect Jumpseller 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.
Coordinate Jumpseller order audits in AutoGen
`list_orders` provides your recent transaction history to initiate a multi-agent debate. A security agent reviews the order totals while a fulfillment agent checks the status, using `get_order` to inspect specific shipping addresses and customer notes. This collaborative workflow ensures no order gets processed without consensus. Your AutoGen agents compare the transaction details against your store guidelines to flag suspicious shipping destinations before dispatch.
Manage Jumpseller inventory via MCP Server
`list_products` pulls your catalog list to let your inventory agent identify low-stock items. If an item needs review, the agent calls `get_product` to fetch current variants, pricing, and image metadata. This MCP Server integration allows a pricing agent and an inventory agent to debate stock adjustments. They evaluate active Jumpseller categories using `list_categories` to decide which product lines require promotional updates.
Validate checkout configurations and shipping rules
`get_store_info` retrieves your core store settings to provide baseline rules for your conversational agents. The agents then call `list_payment_methods` and `list_shipping_methods` to inspect active checkout configurations. A compliance agent reviews these configurations while an operations agent checks for coverage gaps. They negotiate the best setup based on your active Jumpseller rules, preventing checkout errors for international buyers.
Set up Jumpseller 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 Jumpseller 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="Jumpseller_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Jumpseller 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="Jumpseller_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Jumpseller 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 Jumpseller. 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 Jumpseller MCP in AutoGen
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