How to Use the Formbricks MCP in Pydantic AI

Get type-safe feedback management by connecting Pydantic AI to Formbricks for verified, error-free survey handling.

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Connect Formbricks MCP to Pydantic AI

Create your Vinkius account to connect Formbricks to Pydantic AI 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 Pydantic AI

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Type-Safe Survey Operations for Pydantic AI

Stop guessing if your API calls succeeded. Every call to `get_survey` or `list_surveys` is validated against Pydantic models at runtime, so your agent crashes immediately if the API returns malformed data. This enforces strict interface contracts. It prevents silent failures where an agent might otherwise try to process an undefined or corrupted survey field.

Precise Contact Management

Your agent fetches and validates contact metadata with absolute accuracy. Using `get_contact_details`, it populates your Pydantic models with the exact user info needed for follow-up actions. This removes the risk of hallucinated fields. If the CRM record is missing a required piece of data, the agent knows before it attempts to send a response.

Verified Response Retrieval

Get consistent data structures from every survey response. When your agent calls `list_responses`, the results are cast into your defined models, ensuring your downstream logic is always operating on clean data. This makes your feedback pipeline predictable. It uses `get_response` to pull the full payload, and if anything is out of place, the validation layer catches it instantly.

Setup guide

Set up Formbricks MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "formbricks-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Formbricks tools.",
)

result = await agent.run("List recent Formbricks transactions")
print(result.output)

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Common questions about Formbricks MCP in Pydantic AI

You define your Pydantic models, and the toolset automatically validates the JSON output from the MCP server. If the data doesn't match your schema, the agent raises a validation error.

Yes. You get full IDE autocompletion and type checking for every tool. It's the safest way to manage your survey data programmatically.

The server supports both Streamable HTTP and SSE. You just point the client to the URL and it handles the communication layer natively.

Yes. Because the MCP server is model-agnostic, you can use any model that supports the Pydantic AI framework to interact with your survey data.

The server operates in an ephemeral sandbox. It only touches survey responses and contact IDs as requested, and it doesn't cache your sensitive data between agent sessions.

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