How to Use the SimpleFatoora MCP in AutoGen

Q: What happens when I need to validate an API key using SimpleFatoora and AutoGen?

You assign a 'Security Agent' whose sole job is to call validateapikey first. This agent forces the whole conversation to halt if credentials are invalid, preventing bad transactions.

Drive consensus-based decisions with AutoGen and SimpleFatoora's complex e-invoicing tools.

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Setup SimpleFatoora with AutoGen

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Negotiating Invoice Creation

A multi-agent setup can simulate an invoice approval process. One agent might call `create_simplified_invoice`, while another (the 'Compliance Agent') calls `validate_api_key` to ensure the transaction is authorized before final submission. The agents debate the best parameters for the invoice, ensuring all necessary checks pass before the write operation happens.

Product Auditing and Dispute Resolution

If a product needs updating, assign two agents: one calls `get_product` to read current data, and another suggests improvements based on external rules. They argue until they reach consensus on the necessary changes, which is then executed via `update_product`. This mimics real-world review boards that challenge initial assumptions.

Complex Customer Record Management

Managing a customer can't be simple. One agent calls `list_customers`, another checks for duplicates, and a third determines if the record needs creation (`create_customer`) or just an update (`update_customer`). The system converges on the single best action. The negotiation handles edge cases like whether to use `delete_customer` only after confirming all associated invoices are closed.

Setup guide

Set up SimpleFatoora 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 SimpleFatoora 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="SimpleFatoora_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SimpleFatoora. 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 SimpleFatoora MCP in AutoGen

AutoGen's power is in deliberation. Instead of a linear call, multiple agents discuss the required steps—like fetching data, checking rules, then acting—until they achieve consensus on the final action.

You assign a 'Security Agent' whose sole job is to call `validate_api_key` first. This agent forces the whole conversation to halt if credentials are invalid, preventing bad transactions.

Yes. You can set up agents to compare different documentation needs—for instance, arguing whether a B2C invoice (`create_simplified_invoice`) or a B2B VAT invoice (`create_vat_invoice`) is more appropriate based on the input parameters.

The server handles customer details, product listings, and all transaction records (invoices/notes). AutoGen allows you to build a system that constantly verifies compliance across these sensitive datasets.

It's designed for complex operations. The structured tools, like `get_invoice` and `create_standard_purchase`, provide clear inputs and outputs, making them perfect anchors for agent deliberation.

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