How to Use the Hiveage MCP in AutoGen

Q: How do I connect the Hiveage MCP server to my AutoGen agents?

Install the extension using pip install -U "autogen-extmcp". Then configure the connection with mcpservertools and pass the returned tools array directly to your AssistantAgent constructor.

Let your AutoGen agents debate and execute billing operations directly in Hiveage. Automate invoicing without manual data entry.

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Connect Hiveage MCP to AutoGen

Create your Vinkius account to connect Hiveage 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 Hiveage with AutoGen

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Multi-Agent Billing Workflows in AutoGen

Hiveage gives your agents direct access to your accounting data. You set up a finance agent to pull records using `list_invoices` and a client-relations agent to verify the details with `get_customer_details`. They debate the status of overdue accounts before making a move. Once they reach consensus, the system takes action. The agents can trigger `send_invoice_email` to dispatch the finalized bill. You get a conversational audit trail of exactly why an invoice went out, completely replacing static automation scripts with actual reasoning.

Reconcile Payments Automatically

Manual payment matching is a massive time sink. This MCP server lets your agents pull bank feed data and compare it against your ledger using `list_invoice_payments`. If a deposit matches an open bill, the agent flags it for processing. When the agents agree on a match, one of them calls `record_payment`. You just pass the amount, date, and payment method in a JSON string. The ledger updates instantly, keeping your cash flow metrics accurate without human intervention.

Quote Generation via MCP Server

Your sales team needs accurate pricing before sending a proposal. Agents can pull your standard catalog via `list_billing_items` and check current tax rates with `list_tax_profiles`. A sales agent drafts the quote while a finance agent checks the margins. They review past quotes using `list_estimates` and drill into specific line items with `get_estimate_details`. If the numbers look right, the agents finalize the proposal. The entire negotiation happens in the background, so your clients get accurate pricing fast.

Setup guide

Set up Hiveage 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 Hiveage 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="Hiveage_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Hiveage 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="Hiveage_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Install the extension using `pip install -U "autogen-ext[mcp]"`. Then configure the connection with `mcp_server_tools` and pass the returned tools array directly to your AssistantAgent constructor.

The current MCP server configuration handles retrieving and managing existing records. Agents can read data with `get_invoice_details`, record transactions via `record_payment`, and email bills using `send_invoice_email`.

Billing requires absolute accuracy. Having a checker agent verify the output of a drafter agent prevents embarrassing mistakes. They debate the data pulled from `get_customer_details` before anything gets sent to the client.

No. You don't need to write any custom parsers. The McpToolAdapter automatically handles schema translation between the server and your agents. You just provide the endpoint URL and the framework maps the inputs.

This setup processes sensitive customer details, tax profiles, and invoice payment histories. Vinkius runs the integration inside an ephemeral V8 Isolate Sandbox. The environment destroys itself after the agents finish their task, meaning no persistent access to your ledger remains.

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