How to Use the Wherefour MCP in AutoGen

Q: How do I track all sales activity using Wherefour and AutoGen?

You use listorders to pull the raw order list. The agents then discuss which orders are paid, which need follow-up, and what potential issues exist across that set of data.

Q: What is the best way to check customer credit limits using Wherefour and AutoGen?

The system uses listcustomers and then compares those records against listinvoices. The agents debate potential payment risks, giving you a nuanced view of account health.

Q: Do I need to know the specific item ID for checking details with Wherefour and AutoGen?

Yes, for granular detail, you'll use getinventoryitem. The agent needs that identifier to pull the full specs from the system.

Q: If I need a list of all storage locations, what tool should I check with Wherefour and AutoGen?

Use the listlocations tool. It provides a definitive list of every spot you can reference in your multi-agent deliberation.

Force consensus on complex decisions with AutoGen and Wherefour.

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Connect Wherefour MCP to AutoGen

Create your Vinkius account to connect Wherefour 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.

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Setup Wherefour with AutoGen

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Perplexity

Validate Purchase Feasibility

Setup three agents: a 'Purchasing Agent' calls `list_vendors` to check supplier status. A 'Finance Agent' calls `list_purchases` for budget review. Finally, the 'Planner Agent' uses this input to confirm if buying is actually viable. They debate the best course of action, forcing consensus on complex transactions.

Determine Inventory Requirements

An agent checks current stock using `list_inventory_items`. A second agent compares that to needed recipes via `list_formulas`. The third agent then generates a proposed order list by calling `get_order`. This setup mimics a real-world planning committee, negotiating the final required action.

Resolve Fulfillment Discrepancies

One agent reviews the sales orders using `list_orders`. A second agent checks the raw materials available via `get_inventory_item` details. The third agent then debates the discrepancy, reporting what's missing and why. The deliberation process ensures you don't just get data; you get a solution.

Setup guide

Set up Wherefour 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 Wherefour 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="Wherefour_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="Wherefour_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Wherefour 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 Wherefour. 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 Wherefour MCP in AutoGen

You use `list_orders` to pull the raw order list. The agents then discuss which orders are paid, which need follow-up, and what potential issues exist across that set of data.

The system uses `list_customers` and then compares those records against `list_invoices`. The agents debate potential payment risks, giving you a nuanced view of account health.

This MCP Server provides access to inventory items, orders, customers, vendors, stock lots, invoices, purchase records, and formulas. All these topics can be debated among your agents.

Yes, for granular detail, you'll use `get_inventory_item`. The agent needs that identifier to pull the full specs from the system.

Use the `list_locations` tool. It provides a definitive list of every spot you can reference in your multi-agent deliberation.

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