How to Use the Formbricks MCP in Pydantic AI

Get type-safe user feedback with Formbricks and Pydantic AI.

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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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Perplexity

Enforce schema with Pydantic AI models

Every response from `list_responses` is validated against your Pydantic models at runtime. If the API returns junk, the agent errors out before it can process bad data. This guarantees your agent logic never breaks due to unexpected API changes. You get strict, predictable data handling every time.

Map actions for Pydantic AI agents

Use `list_action_classes` to define the triggers for your surveys. Your agent validates these actions against your model to ensure the survey only fires on legitimate user events. It removes the risk of hallucinated survey triggers. You define the rules, and the agent follows them exactly.

Audit your feedback with Pydantic AI

Chain `get_survey` and `get_person` to verify feedback integrity. Because you use Pydantic, you know exactly what fields exist before your agent tries to read them. This makes debugging your feedback loop trivial. You see exactly where the data fails validation instead of hunting through logs.

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-alternative-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

It provides runtime validation for all MCP responses. You won't have to worry about silent failures when fetching survey data.

Not at all. Install the Pydantic AI MCP client and point it at the HTTP endpoint. The types are inferred automatically.

The server only handles survey-related payloads. It doesn't touch your internal user tables, ensuring your core data stays isolated.

The agent will raise a validation error instantly. This prevents corrupted data from entering your processing pipeline.

Yes. Pydantic AI is model-agnostic. As long as your agent can talk to the MCP server, you can use any local or remote model.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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