How do I get an Access Token for GetFeedback?

Log in to GetFeedback, navigate to your account settings or profile, and look for the API section to generate your Personal Access Token.

Can I see incomplete survey responses?

Yes! The 'list_survey_responses' tool allows you to filter by status. You can view responses that were 'started' but not yet finished, as well as 'completed' ones.

How do I send a survey to a list of people?

Use the 'send_survey_invites' tool. Provide the Survey ID and a JSON array of email addresses to trigger the invitations instantly.

Is the data returned in real-time?

Yes, all feedback data retrieved through this MCP server is fetched directly from the GetFeedback Reporting API, providing you with the latest available records.

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

Name: GetFeedback
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 GetFeedback 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 GetFeedback "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

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Ed25519Audit chain

<40msKill switch

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 GetFeedback MCP Server

Connect your GetFeedback account to any AI agent to automate your customer feedback and survey reporting workflows through the Model Context Protocol (MCP). GetFeedback is a powerful, mobile-friendly survey platform that helps brands collect and analyze customer sentiment in real-time. This MCP server enables you to retrieve survey results, monitor completion statuses, and trigger survey invitations directly through natural conversation.

Pydantic AI validates every GetFeedback 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.

Key Features

Survey Orchestration — List all active surveys in your account and fetch detailed structural metadata for each form.
Real-time Response Tracking — Retrieve customer feedback as it arrives, including detailed answer payloads and completion timestamps.
Advanced Filtering — List survey responses filtered by status (started, completed) or created after a specific date for targeted reporting.
Automated Invitations — Trigger survey emails to a list of recipients programmatically from your chat interface.
Identity Oversight — Access global profile information for the authenticated GetFeedback user to ensure correct account context.
Data Connectivity — Verify your API connection and account health to maintain seamless feedback loops.
Asynchronous Monitoring — Fetch high-level response counts and status metrics to track survey performance instantly.

The GetFeedback 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 GetFeedback to Pydantic AI via MCP

Follow these steps to integrate the GetFeedback 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 GetFeedback with type-safe schemas

Why Use Pydantic AI with the GetFeedback MCP Server

Pydantic AI provides unique advantages when paired with GetFeedback 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 GetFeedback integration code

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

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

GetFeedback + Pydantic AI Use Cases

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

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

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

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

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

GetFeedback MCP Tools for Pydantic AI (12)

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

check_api_limits

Verify connectivity

get_my_identity

Get user identity

get_response_details

Get response metadata

get_survey_details

Get survey metadata

get_survey_stats

Get response count

list_completed_feedback

Filter for completed

list_feedback_page

Paginated responses

list_recent_feedback

Filter by date

list_survey_responses

List feedback data

list_surveys

List all surveys

send_survey_invites

Trigger survey email

verify_api_connection

Check connection

Example Prompts for GetFeedback in Pydantic AI

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

"List all active surveys in my GetFeedback account."

"Show me the last 5 completed responses for survey '12345'."

"Send the 'Onboarding Survey' (ID: 98765) to ['user1@test.com', 'user2@test.com']."

Troubleshooting GetFeedback MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

GetFeedback + Pydantic AI FAQ

Common questions about integrating GetFeedback 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 GetFeedback MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.