How to Use the Alegra MCP in AutoGen

Build multi-agent AutoGen teams that debate and resolve Alegra invoicing, billing, and tax compliance tasks.

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Connect Alegra MCP to AutoGen

Create your Vinkius account to connect Alegra 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 Alegra with AutoGen

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Resolve billing disputes via AutoGen debate

Coordinate billing dispute resolutions by letting one AutoGen agent run `list_payments` while another checks client terms via `get_contact_details`. Deliberating on these records helps them find discrepancies before taking action. Instead of blindly running a tool, the AutoGen billing agent proposes `create_invoice` and waits for the compliance agent to sign off on the tax rules.

Validate tax compliance with an MCP Server

Check company details using `get_company_info` to satisfy strict Latin American tax regulations inside your AutoGen group chat. One agent checks the customer's tax ID via `list_contacts` while a peer agent validates the corporate profile. The agents must agree on the tax configuration before issuing documents. If there is a mismatch, the AutoGen agents discuss the issue in the chat log before calling `create_contact` to update the record.

Coordinate inventory and estimate updates

Track stock levels via `list_inventory_items` to keep your sales pipeline in sync with your warehouse using AutoGen conversation flows. A warehouse agent tracks stock levels and updates a sales agent when items run low. The sales agent then uses `list_estimates` to find drafts that need adjustment. Because of this AutoGen multi-agent coordination, you never promise inventory you do not have in stock.

Setup guide

Set up Alegra 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 Alegra 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="Alegra_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install the autogen-ext package and use the streamable HTTP client to connect to Vinkius. Pass the converted tools list directly to your AssistantAgent constructor. This gives your agents access to actions like `create_invoice` instantly.

Yes, you can set up a multi-agent group chat. One agent drafts the invoice using `create_invoice`, while a manager agent reviews the details using `get_invoice_details` before finalizing.

Your agents can split the work. One queries your bank log, another calls `list_payments`, and they compare the records. They only log a match when both agree the balance is settled.

Yes, the connection handles streaming tool execution outputs. Your agents receive instant feedback when calling `list_estimates` or `get_item_details` during their multi-turn conversations via the MCP adapter.

Your invoices, payment histories, and customer contacts are fully protected. Vinkius hosts this MCP Server in an isolated, secure sandbox with end-to-end encryption. Your credentials never touch the LLM provider, ensuring your business accounting remains completely private.

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