How do I obtain my Fairing API Key?

You can find your API Key in the Fairing admin portal under **Settings > Account**. Note that API access may depend on your current subscription plan.

Can I see responses for a specific customer?

Yes! Use the `get_customer_responses` tool with the specific Customer ID to retrieve all survey feedback associated with that individual.

What kind of insights can I extract?

The `get_insights` tool provides aggregated data on question performance, response rates, and attribution trends across your survey streams.

Fairing MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Fairing
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Fairing "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Fairing MCP Server

Connect your Fairing (formerly EnquireLabs) account to any AI agent and take full control of your post-purchase surveys and zero-party data through natural conversation.

Pydantic AI validates every Fairing tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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 & Question Management — List all active questions and fetch detailed configurations for your post-purchase surveys
Response Tracking — List and inspect individual survey responses to understand customer sentiment and attribution
Zero-Party Data Analysis — Query customer-specific responses to pair survey data with your marketing profiles
Aggregated Insights — Extract high-level insights and performance metrics across all your survey streams
Integration Audit — Monitor active integrations with platforms like Klaviyo, GA4, and Meta directly from the cloud
Account Context — Retrieve your Fairing account details and API token identity flawlessly

The Fairing MCP Server exposes 12 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.

How to Connect Fairing to Pydantic AI via MCP

Follow these steps to integrate the Fairing MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

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

Explore tools

The agent discovers 12 tools from Fairing with type-safe schemas

Why Use Pydantic AI with the Fairing MCP Server

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

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

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

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

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

Fairing + Pydantic AI Use Cases

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

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

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

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

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

Fairing MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Fairing to Pydantic AI via MCP:

get_account_info

Get Fairing account information

get_customer_responses

Get all survey responses for a specific customer

get_insights

Get aggregated survey insights

get_me

Get current API token identity

get_question

Get details for a specific survey question

get_response

Get details for a specific survey response

get_survey_details

Get details for a specific survey

list_customers

List customers who have interacted with surveys

list_integrations

List active Fairing integrations

list_questions

List all Fairing survey questions

list_responses

List all survey responses

list_surveys

List all Fairing surveys

Example Prompts for Fairing in Pydantic AI

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

"List all active survey questions on Fairing."

"Show me the latest 5 survey responses."

"Check my active integrations on Fairing."

Troubleshooting Fairing MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Fairing + Pydantic AI FAQ

Common questions about integrating Fairing MCP Server with Pydantic AI.

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.

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.

Can I switch LLM providers without changing MCP code?

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