Shoplazza / 店匠 MCP Server for AutoGen 10 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Shoplazza / 店匠 as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="shoplazza_agent",
tools=tools,
system_message=(
"You help users with Shoplazza / 店匠. "
"10 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* 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 Shoplazza / 店匠 MCP Server
Empower your AI agent to orchestrate your global retail business with Shoplazza (店匠), the premier E-commerce platform for international brands. By connecting Shoplazza to your agent, you transform complex store management and order tracking into a natural conversation. Your agent can instantly list your products, retrieve detailed order information, monitor inventory levels, and even browse store collections without you ever needing to navigate the Shoplazza Admin interface. Whether you are managing a single boutique or a large-scale international operation, your agent acts as a real-time retail assistant, keeping your data accurate and your global sales moving.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Shoplazza / 店匠 tools. Connect 10 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Product Orchestration — List all items in your store, get detailed product metadata, and browse collections.
- Order Management — List and retrieve detailed order information to track fulfillment, payments, and delivery.
- Inventory Monitoring — Retrieve real-time inventory levels for your products to ensure stock availability.
- Customer Insights — Search and manage customer profiles and their purchase history.
- Store Configuration — Access general shop information and monitor configured webhooks.
The Shoplazza / 店匠 MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen 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 Shoplazza / 店匠 to AutoGen via MCP
Follow these steps to integrate the Shoplazza / 店匠 MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 10 tools from Shoplazza / 店匠 automatically
Why Use AutoGen with the Shoplazza / 店匠 MCP Server
AutoGen provides unique advantages when paired with Shoplazza / 店匠 through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Shoplazza / 店匠 tools to solve complex tasks
Role-based architecture lets you assign Shoplazza / 店匠 tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Shoplazza / 店匠 tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Shoplazza / 店匠 tool responses in an isolated environment
Shoplazza / 店匠 + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Shoplazza / 店匠 MCP Server delivers measurable value.
Collaborative analysis: one agent queries Shoplazza / 店匠 while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Shoplazza / 店匠, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Shoplazza / 店匠 data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Shoplazza / 店匠 responses in a sandboxed execution environment
Shoplazza / 店匠 MCP Tools for AutoGen (10)
These 10 tools become available when you connect Shoplazza / 店匠 to AutoGen via MCP:
get_customer
Get customer details
get_inventory_levels
Get inventory levels
get_order
Get order details
get_product
Get product details
get_shop_info
Get shop information
list_collections
List product collections
list_customers
List shop customers
list_orders
List shop orders
list_products
List shop products
list_webhooks
List store webhooks
Example Prompts for Shoplazza / 店匠 in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Shoplazza / 店匠 immediately.
"List all products in my Shoplazza store."
"Show me the last 5 orders from my Shoplazza shop."
"Check the inventory level for item ID 'inv-123456'."
Troubleshooting Shoplazza / 店匠 MCP Server with AutoGen
Common issues when connecting Shoplazza / 店匠 to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Shoplazza / 店匠 + AutoGen FAQ
Common questions about integrating Shoplazza / 店匠 MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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Microsoft's framework for multi-agent collaborative conversations.
Connect Shoplazza / 店匠 to AutoGen
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.