How to Use the Medallia MCP in Pydantic AI

Q: Can I use Pydantic AI to filter specific Medallia surveys?

Yes, your agent can call listsurveys to find active questionnaires and then use type-safe arguments to fetch specific details with getsurvey. The framework validates all input parameters before sending the API request.

Get type-safe Medallia feedback data in Pydantic AI with strict runtime validation using this MCP Server.

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Connect Medallia MCP to Pydantic AI

Create your Vinkius account to connect Medallia to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Medallia with Pydantic AI

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Type-safe survey analysis with Pydantic AI

Using the `get_response` tool, your Pydantic AI agent ensures every customer reply is validated against strict models at runtime. It'll pull feedback via `list_responses` and guarantee you don't face silent data corruption. This MCP Server ensures that every response pulled via `get_response` or `list_responses` is validated against strict Pydantic models at runtime. If the Medallia API returns unexpected schema changes, your Pydantic AI agent fails loudly and immediately.

Validate alert structures before execution

By calling `list_alerts`, your Pydantic AI agent fetches active Medallia issues with every field verified against runtime type definitions. It'll grab details with `get_alert` so you don't pass malformed data to your ticketing systems. This strict validation prevents your Pydantic AI agent from passing malformed Medallia data to your ticketing systems. You can confidently automate alert routing, knowing that every customer profile and survey ID matches your exact database schema.

Reliable program and user audits

Using the `list_programs` tool, your Pydantic AI agent queries experience management programs with clean, validated data structures. It'll check user access controls with `list_users` to verify active programs safely. Pydantic AI handles the validation of these lists, ensuring that Medallia user roles and program details are parsed correctly. This setup eliminates the risk of your agent making decisions based on partially parsed or corrupted API outputs.

Setup guide

Set up Medallia MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "medallia-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Medallia tools.",
)

result = await agent.run("List recent Medallia transactions")
print(result.output)

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Common questions about Medallia MCP in Pydantic AI

Install the slim package with the MCP extra and initialize the connection using `MCPToolset`. Pass this toolset instance directly into your Agent's `toolsets` argument to expose all ten feedback tools.

Pydantic AI will raise a validation error at runtime instead of letting the agent process corrupted data. This ensures your systems fail safely rather than executing actions based on misaligned survey or alert fields.

Yes, your agent can call `list_surveys` to find active questionnaires and then use type-safe arguments to fetch specific details with `get_survey`. The framework validates all input parameters before sending the API request.

The server supports both Streamable HTTP and SSE transports. Since the server runs externally, you should configure the toolset with the HTTP endpoint provided by your Vinkius dashboard.

The server processes all survey text and user metadata through an ephemeral, zero-trust V8 sandbox. Your credentials and customer experience data are never stored, logged, or shared with third parties.

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