How to Use the Treinta App MCP in AutoGen

Q: When using Treinta App and AutoGen, what is the data privacy guarantee?

The server touches client debt profiles (getclient). The agents operate within a zero-trust framework, ensuring every interaction requires an endpoint token for security.

Q: Can AutoGen handle both sales listing and transaction deletion?

Yes. One agent gathers historical data using listsales, while a second agent debates whether an incorrect record requires intervention, ultimately calling deletetransaction.

Facilitate consensus-driven decisions on Treinta App operations with AutoGen agents.

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Connect Treinta App MCP to AutoGen

Create your Vinkius account to connect Treinta App 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 Treinta App with AutoGen

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Perplexity

AutoGen: Debate sales feasibility and client status.

You can set up multiple agents to debate a transaction. One agent calls `get_client` to check the debt profile, while another checks `list_sales`. They then negotiate whether or not the system should proceed with a `create_transaction`. This simulates complex human oversight where consensus is required before action.

AutoGen: Negotiate inventory updates and product status.

Need to handle a major stock change? Have one agent check the current product details using `get_product`. A second agent checks the global `list_products` list for consistency. They debate the necessity of an `update_product_stock`, converging on the final action. It's perfect when decisions rely on conflicting data points.

AutoGen: Coordinate complex ledger reporting.

A system can use multiple agents to compile a report. Agent A calls `list_transactions` for book flow. Agent B calls `get_business_stats`. They debate which metrics are most relevant and assemble the final, comprehensive dashboard output. This moves beyond simple sequential calling into true deliberation.

Setup guide

Set up Treinta App 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 Treinta App 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="Treinta App_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You can configure agents to debate transaction risks. One agent calls `get_client` and another checks the P&L via `get_business_stats`. They argue until a decision is reached, mimicking human sign-off.

Yes. You can set up agents that debate whether the business needs to call `create_client` first, or if it should focus on adding new inventory via `create_product`. The system determines priority.

The server touches client debt profiles (`get_client`). The agents operate within a zero-trust framework, ensuring every interaction requires an endpoint token for security.

Absolutely. You can run two competing agents: one that calls `list_products` and another that tries to call `update_product_stock`. They debate the appropriate final stock figure.

Yes. One agent gathers historical data using `list_sales`, while a second agent debates whether an incorrect record requires intervention, ultimately calling `delete_transaction`.

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