How to Use the Formbricks MCP in AutoGen

Q: How do I register Formbricks tools in AutoGen?

Use mcpservertools with a StreamableHttpServerParams configuration. AutoGen's McpToolAdapter converts the schema automatically for your AssistantAgent to interact with the MCP Server.

Q: Can AutoGen agents argue over Formbricks data?

Yes. You assign one agent to read listresponses and another to critique the findings. They debate the feedback until they reach a consensus.

Q: Can agents read user profiles?

They execute listpeople to see who interacts with your application. This helps them segment feedback based on user activity.

Let AutoGen agents debate user feedback and deploy targeted Formbricks surveys autonomously.

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Connect Formbricks MCP to AutoGen

Create your Vinkius account to connect Formbricks 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 Formbricks with AutoGen

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Perplexity

Deploy Surveys via Consensus

Your AutoGen agents debate when to interrupt a user before calling `create_survey`. A product agent argues for maximum data collection, while a UX agent pushes back to minimize friction. They reach an agreement and configure the exact trigger moment using `list_action_classes`. You get a feedback loop managed by competing priorities, ensuring you only ask questions when it makes sense.

Analyze Responses as a Team

Multiple agents collaborate to process data pulled from `list_responses` and `get_response`. One agent summarizes the raw text, while a second agent challenges the interpretation based on historical data. They pull additional context by running `get_person` to see who left the feedback. The final output you receive is a heavily debated, highly accurate summary of user sentiment.

Audit the Formbricks MCP Server

A dedicated security agent monitors your feedback infrastructure by executing `list_webhooks` and `list_surveys`. It ensures no unauthorized endpoints are receiving customer data. If the team detects a redundant or underperforming prompt, an agent calls `delete_survey` to keep the system clean. The multi-agent setup governs your entire survey lifecycle.

Setup guide

Set up Formbricks 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 Formbricks 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="Formbricks_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Use mcp_server_tools with a StreamableHttpServerParams configuration. AutoGen's McpToolAdapter converts the schema automatically for your AssistantAgent to interact with the MCP Server.

Yes. You assign one agent to read list_responses and another to critique the findings. They debate the feedback until they reach a consensus.

Only if you authorize it. The agents can propose running create_survey, but you can require human-in-the-loop approval before the execution happens.

They execute list_people to see who interacts with your application. This helps them segment feedback based on user activity.

Vinkius hosts the connection in a strict V8 Isolate Sandbox. When your agents fetch list_action_classes, the data moves through a zero-trust environment and the container vanishes after execution.

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