How to Use the Evoliz Invoicing & Management MCP in AutoGen

Q: Is my Evoliz Invoicing & Management account metadata private in AutoGen?

Yes, sensitive account information retrieved via getevolizaccountmetadata remains scoped to your specific agent session and is not logged or shared.

Debate financial decisions in AutoGen. Use Evoliz Invoicing & Management tools to reach consensus on client billing.

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Connect Evoliz Invoicing & Management MCP to AutoGen

Create your Vinkius account to connect Evoliz Invoicing & Management 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 Evoliz Invoicing & Management with AutoGen

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Perplexity

Multi-agent billing debates in AutoGen

Deploy an agent to call `list_unpaid_overdue_invoices` while another agent reviews client history via `get_client_detailed_profile`. They argue over the best collection strategy based on the data. This forces a consensus before any action is taken. You get a balanced approach to managing overdue accounts that considers both revenue and client relations.

Cross-check invoices with AutoGen

Assign one agent to check `list_sales_invoices` and another to verify details with `get_invoice_detailed_data`. They reconcile the records to ensure accuracy. This automated check prevents errors in your financial reporting. If the agents disagree, they flag the discrepancy for your human review.

Negotiate quotes with AutoGen

Let agents analyze `list_sales_quotes` and `list_product_catalog` to determine if a quote is competitive. They debate the pricing strategy based on the data retrieved. You define the constraints, and the agents negotiate the logic. It results in a firm decision backed by your actual product pricing.

Setup guide

Set up Evoliz Invoicing & Management 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 Evoliz Invoicing & Management 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="Evoliz Invoicing & Management_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Evoliz Invoicing & Management 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="Evoliz Invoicing & Management_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Evoliz Invoicing & Management 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 Evoliz Invoicing & Management. 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 Evoliz Invoicing & Management MCP in AutoGen

Use the MCP adapter to expose the tools to your agents. You then assign specific tools to individual agents to manage their responsibilities.

Agents utilize the tools to gather evidence for their arguments. This allows for data-driven consensus on complex tasks like invoice collection.

The Vinkius platform handles all authentication and transport. Your financial metadata and invoice records are processed within a secure, isolated environment.

Only the agents you explicitly grant tool access can see the data. The server manages access via secure, scoped tokens.

Yes, sensitive account information retrieved via `get_evoliz_account_metadata` remains scoped to your specific agent session and is not logged or shared.

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