How to Use the Flodesk MCP in AutoGen

Q: How do AutoGen agents handle Flodesk custom fields?

One agent can list fields using listcustomfields, while a data-entry agent uses createcustomfield to set up new attributes based on their collective decision.

Let your AutoGen agents debate and optimize your Flodesk marketing campaigns before executing updates.

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Connect Flodesk MCP to AutoGen

Create your Vinkius account to connect Flodesk 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 Flodesk with AutoGen

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AutoGen multi-agent consensus

Verify subscriber opt-in status before calling `create_subscriber` by running a multi-agent compliance check. In AutoGen, you can set up a copywriter agent, a targeting agent, and a compliance agent to run safer marketing automations with multiple agents using this MCP Server. This prevents compliance mistakes. If the compliance agent flags a risk, the system halts. Once they agree, the execution agent calls `add_to_segment` to finalize the update.

Automated list cleaning debates

Pull inactive users via `list_subscribers` and let your agents discuss whether to prune them or try a re-engagement workflow. One agent can pull inactive users, while another checks their engagement history. If they decide to prune, they call `unsubscribe_subscriber`. If they choose to re-engage, they call `trigger_workflow`. This multi-agent setup ensures you don't delete valuable contacts on a single heuristic.

Managed segment growth

Monitor your opt-in forms using `list_forms` with an AutoGen team to track sign-up trends. One agent analyzes sign-up trends while another updates your targeting parameters. They use `create_custom_field` to build new tracking metrics based on their findings. The agents work together via the MCP interface to ensure your Flodesk account structure matches your actual business growth.

Setup guide

Set up Flodesk 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 Flodesk 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="Flodesk_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Flodesk. 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 Flodesk MCP in AutoGen

Use the MCP tool adapter to convert the server tools. You can pass the resulting tool list directly to your AssistantAgent constructor, enabling actions like `create_subscriber`.

Yes. A coordinator agent can analyze subscriber segments using `list_segments` and instruct a sender agent to call `trigger_workflow` for the qualified users.

One agent can list fields using `list_custom_fields`, while a data-entry agent uses `create_custom_field` to set up new attributes based on their collective decision.

The execution agent will report the error back to the group. The supervisor agent can then log the issue or attempt a retry of `unsubscribe_subscriber` with corrected parameters.

Your subscriber records, custom field mappings, and workflow histories are protected by Vinkius's ephemeral V8 isolate MCP architecture. No data is cached or stored outside the active agent conversation session.

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