How to Use the Tally MCP in AutoGen

Q: If I run a multi-agent workflow with AutoGen, what Tally tools are used?

The system uses all available tools: listworkspaces for scope mapping, getform for structure details, and getsubmission to retrieve specific record content based on the debate's findings.

Debate Data Integrity with AutoGen: Consensus on Tally Forms and Submissions.

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Setup Tally with AutoGen

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Multi-Agent Workflow for MCP Server

You set up multiple agents to work together, like a 'Validator Agent' calling `get_form` and an 'Auditor Agent' checking submissions with `list_submissions`. The system forces them to debate the correct course of action. This means you don't just get one answer. You get consensus: Agent A suggests deleting data using `delete_submission`, but Agent B flags a risk, forcing a review that yields a final, agreed-upon decision.

Gathering Comprehensive Tally Data with AutoGen

One agent can use `list_workspaces` to map the scope of operations. Another agent might then call `get_me` to confirm user permissions before proceeding. The conversation flow makes it robust: if the 'Permissions Agent' finds a gap, it halts the process and requests more information from the user, ensuring all necessary data—like specific form IDs via `list_forms`—is collected.

Managing Tally Forms Through Debate

The agents can simulate different scenarios. For instance, one agent might propose deleting old records using `delete_submission`, while another challenges that action by calling `get_submission` on a sample record to verify its importance. This debate structure is perfect when the optimal path isn't obvious; it forces deep scrutiny of every tool call and data point.

Setup guide

Set up Tally 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 Tally 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="Tally_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Common questions about Tally MCP in AutoGen

AutoGen allows multiple agents to review the process. You can have one agent list all forms (`list_forms`) while another checks permissions using `get_me`. They debate the best sequence, leading to a fully validated execution plan.

Yes. If an agent suspects bad data, it can propose the use of `delete_submission`, which then triggers a debate among other agents to confirm if deletion is appropriate before executing.

The system uses all available tools: `list_workspaces` for scope mapping, `get_form` for structure details, and `get_submission` to retrieve specific record content based on the debate's findings.

The system handles form metadata (structure), workspace details, user account information (`get_me`), and the actual structured content of Tally submissions. The debate process ensures all these inputs are considered.

It requires the standard outputs from the MCP Server, such as form IDs or workspace IDs obtained from `list_forms` and `list_workspaces`. The agents handle passing these identifiers between conversations.

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