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Formbricks MCP Server for Pydantic AIGive Pydantic AI instant access to 10 tools to Create Survey, Delete Survey, Get Person, and more

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Formbricks through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Formbricks app connector for Pydantic AI is a standout in the Customer Support category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Formbricks "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Formbricks?"
    )
    print(result.data)

asyncio.run(main())
Formbricks
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Formbricks MCP Server

Connect your Formbricks environment to any AI agent and simplify your feedback collection and survey management through natural conversation.

Pydantic AI validates every Formbricks tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

  • Survey Control — List all surveys, check their status, and create or delete survey structures programmatically
  • Response Management — Query results for any survey to analyze user feedback and submission data
  • People Insights — List identified contacts and retrieve their metadata and custom attributes
  • Workflow Monitoring — Inspect configured webhooks and action classes to understand your data flow

The Formbricks MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 Formbricks tools available for Pydantic AI

When Pydantic AI connects to Formbricks through Vinkius, your AI agent gets direct access to every tool listed below — spanning user-feedback, experience-management, survey-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_survey

Create a new survey

delete_survey

Delete a survey

get_person

Get details for a specific person

get_response

Get details for a specific response

get_survey

Get details for a specific survey

list_action_classes

List action classes

list_people

List identified people

list_responses

Optionally filter by a specific survey ID. List survey responses

list_surveys

List all surveys

list_webhooks

List configured webhooks

Connect Formbricks to Pydantic AI via MCP

Follow these steps to wire Formbricks into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 10 tools from Formbricks with type-safe schemas

Why Use Pydantic AI with the Formbricks MCP Server

Pydantic AI provides unique advantages when paired with Formbricks through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Formbricks integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Formbricks connection logic from agent behavior for testable, maintainable code

Formbricks + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Formbricks MCP Server delivers measurable value.

01

Type-safe data pipelines: query Formbricks with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Formbricks tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Formbricks and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Formbricks responses and write comprehensive agent tests

Example Prompts for Formbricks in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Formbricks immediately.

01

"List all surveys in Formbricks."

02

"Show me responses for the NPS survey."

03

"Get metadata for person 'user_555'."

Troubleshooting Formbricks MCP Server with Pydantic AI

Common issues when connecting Formbricks to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Formbricks + Pydantic AI FAQ

Common questions about integrating Formbricks MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Formbricks MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.