How to Use the Flowcode MCP in AutoGen

Q: How is my Flowcode demographic and audience data protected in AutoGen?

Demographic summaries from getaudiencesummary are processed locally within your Python runtime. Vinkius handles the API connection over an encrypted tunnel, ensuring your customer demographics are never exposed.

Deploy AutoGen agent teams to debate marketing performance and generate optimized Flowcode dynamic QR campaigns.

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Connect Flowcode MCP to AutoGen

Create your Vinkius account to connect Flowcode 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 Flowcode with AutoGen

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Debate Performance and Generate Assets

The `create_flowcode` tool allows your AutoGen agent team to generate new dynamic QR codes after negotiating campaign strategy. One agent can propose a new code layout while a safety agent checks the destination URL before execution. This conversational workflow ensures you never print a broken or unapproved QR code. The agents reach a consensus on the target URL, then trigger the creation tool automatically.

Analyze CRM Contacts via Multi-Agent Debate

The `get_flowpage_contacts` tool pulls lead generation data directly into your AutoGen agent conversations. Your sales agent and marketing agent can debate how to segment these contacts based on their acquisition source using this MCP Server. Instead of manual export-import, the agents discuss the leads in real time. They compare the contact list against active campaigns to determine which physical locations yield the highest quality leads.

Optimize Campaigns with AutoGen MCP Server Tools

The `list_conversion_rates` tool provides the hard funnel data your AutoGen agents need to settle performance disputes. A budget agent might argue to cut physical media spend, while a brand agent points to these conversion rates to justify the campaign. This data-driven debate leads to better strategic decisions. The agents analyze the conversion metrics, agree on the best path forward, and update your active campaigns.

Setup guide

Set up Flowcode 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 Flowcode 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="Flowcode_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You register the server's tools with your agent group. One agent can call `get_audience_summary` to analyze demographics, while another uses that analysis to draft a new campaign strategy.

Yes, you can configure a supervisor agent to audit parameters before `create_flowcode` runs. If the destination URL fails validation, the agent blocks the tool call.

AutoGen's conversation logs record the exact sender and tool call history. You see which agent triggered `get_flowpage_analytics` and how other agents responded to that data.

Yes, you can set up a multi-agent loop where one agent lists assets using `list_flowcodes` and another checks their active status. They compile a report on unused or underperforming codes via the MCP Server.

Demographic summaries from `get_audience_summary` are processed locally within your Python runtime. Vinkius handles the API connection over an encrypted tunnel, ensuring your customer demographics are never exposed.

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