QuestionPro MCP Server for Pydantic AIGive Pydantic AI instant access to 13 tools to Check Questionpro Status, Create Survey, Get Question, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect QuestionPro 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 QuestionPro app connector for Pydantic AI is a standout in the Data Analytics category — giving your AI agent 13 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 QuestionPro "
"(13 tools)."
),
)
result = await agent.run(
"What tools are available in QuestionPro?"
)
print(result.data)
asyncio.run(main())
* 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 QuestionPro MCP Server
Bring advanced survey analytics into your AI workflow with QuestionPro. Your agents can orchestrate end-to-end feedback loops by filtering folders for active campaigns, compiling real-time response statistics, retrieving granular participant data, and maintaining contact lists—all executed conversationally.
Pydantic AI validates every QuestionPro tool response against typed schemas, catching data inconsistencies at build time. Connect 13 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
- Create, retrieve, and organize surveys with folder filtering
- Analyze real-time survey statistics and completion rates
- Collect and inspect individual respondent data
- Manage question banks and user administration
- Organize email outreach lists efficiently
Who is it for?
Ideal for market researchers, HR teams, and product managers needing fast, AI-driven insights from customer and employee feedback.The QuestionPro MCP Server exposes 13 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 13 QuestionPro tools available for Pydantic AI
When Pydantic AI connects to QuestionPro through Vinkius, your AI agent gets direct access to every tool listed below — spanning market-research, customer-feedback, employee-engagement, 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.
Verify connectivity
Create a survey
Get question details
Get response details
Get survey details
Get survey statistics
List email lists
List folders
List survey questions
List survey responses
List surveys
List surveys by folder
List account users
Connect QuestionPro to Pydantic AI via MCP
Follow these steps to wire QuestionPro into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the QuestionPro MCP Server
Pydantic AI provides unique advantages when paired with QuestionPro 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 QuestionPro integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your QuestionPro connection logic from agent behavior for testable, maintainable code
QuestionPro + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the QuestionPro MCP Server delivers measurable value.
Type-safe data pipelines: query QuestionPro with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple QuestionPro tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query QuestionPro and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock QuestionPro responses and write comprehensive agent tests
Example Prompts for QuestionPro in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with QuestionPro immediately.
"Show response rate and completion stats for our customer satisfaction survey"
"Show me all active surveys with their response rates and completion percentages."
"Export the detailed analytics report for the Customer Experience 2025 survey."
Troubleshooting QuestionPro MCP Server with Pydantic AI
Common issues when connecting QuestionPro to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiQuestionPro + Pydantic AI FAQ
Common questions about integrating QuestionPro MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.