How do I get my Medallia API credentials?

You need to contact your Medallia administrator to enable the REST API and create an OAuth 2.0 application to receive your Client ID and Secret.

What survey data can I access?

You can access survey configurations, individual responses, scores (like NPS), feedback comments, and metadata associated with each response.

Is my customer data secure?

Absolutely. Your credentials are encrypted at rest and injected securely at runtime.

Medallia MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Medallia
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Medallia 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 Medallia "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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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 Medallia MCP Server

Connect your Medallia experience management instance to any AI agent and take full control of your customer feedback and CX programs through natural conversation.

Pydantic AI validates every Medallia 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 Management — List all customer surveys and fetch detailed configuration metadata
Feedback Monitoring — Retrieve and search survey responses to understand customer sentiment in real-time
Program Oversight — List and inspect experience management programs and their statuses
Alert Management — Monitor and retrieve details for alerts triggered by specific customer feedback
User Inventory — List authorized users and manage access within your Medallia instance

The Medallia 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.

How to Connect Medallia to Pydantic AI via MCP

Follow these steps to integrate the Medallia 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 10 tools from Medallia with type-safe schemas

Why Use Pydantic AI with the Medallia MCP Server

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

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

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

Medallia + Pydantic AI Use Cases

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

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

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

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

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

Medallia MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Medallia to Pydantic AI via MCP:

get_alert

Get details for a specific alert

get_program_details

Get details for a specific program

get_response

Get details for a specific response

get_survey

Get details for a specific survey

list_alerts

List feedback alerts

list_programs

List experience management programs

list_responses

List survey responses

list_surveys

List all customer surveys

list_users

List Medallia users

search_responses

Search survey responses by term

Example Prompts for Medallia in Pydantic AI

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

"List all active surveys in Medallia."

"Search responses for the term 'disappointed'."

"Show recent alerts from high-priority programs."

Troubleshooting Medallia MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Medallia + Pydantic AI FAQ

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