How to Use the Custify MCP in AutoGen

Enable multi-agent debate in AutoGen using live Custify account metrics.

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Connect Custify MCP to AutoGen

Create your Vinkius account to connect Custify 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 Custify with AutoGen

Ask AI about this MCP

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Claude

Perplexity

Debate Custify data between AutoGen agents

One agent calls `list_customer_success_tasks` while another analyzes the priorities. They argue about the best course of action until they reach a consensus. This approach ensures that your customer strategy isn't based on a single agent's bias. You get balanced decisions backed by real data from your account.

Negotiate Custify updates with AutoGen

A security agent can flag risk while a sales agent calls `get_company_details` to verify the account status. They deliberate until the risk is addressed. Your system handles complex workflows where multiple perspectives matter. The MCP Server provides the raw data that triggers these internal negotiations.

Automate Custify workflows with multi-agent consensus

Use `create_customer_profile` after your agents agree on the necessary data points. The agents verify the validation status before finalizing the record. You build systems that handle nuanced tasks requiring human-like deliberation. The agents check each other's work using the provided toolset.

Setup guide

Set up Custify 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 Custify 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="Custify_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install the MCP extension and pass the server tools to your AssistantAgent. The adapter automatically handles the schema conversion for you.

They can. You can configure one agent to prioritize health scores from `get_customer_details` while another focuses on task completion, forcing a debate.

It supports both stdio and HTTP transports. Your agents can call any of the ten available tools as part of their conversation loop.

Provide clear instructions in your system prompt. Since the tools are provided as an MCP Server, the agents understand the input schema and required arguments.

We maintain a zero-trust environment for your interactions. The server only interacts with your internal CRM notes and customer records, ensuring your data remains isolated.

Use it with your favorite AI tools

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