How to Use the Showpad MCP in Pydantic AI

Q: How does Pydantic AI make Showpad asset searches reliable?

The agent calls searchassets and immediately validates the output against a schema. This means you're never dealing with messy, unstructured search results; the data is always predictable.

Q: If I use Pydantic AI, how do I check Showpad user records?

You call listusers to get IDs. Then, using getuserdetails, your agent gets the profile data. The validation layer confirms that every field—name, title, email—is present and correctly typed.

Q: What happens if Showpad changes its content structure with Pydantic AI?

Nothing breaks silently. If the underlying API for listassets suddenly returns an unexpected field or removes a required one, your agent fails immediately with a clear validation error. You're alerted to the issue right away.

Q: Can Pydantic AI help me map out Showpad content tags?

Yes. The listtags tool provides the list, and your agent can then validate that these tags follow a consistent naming pattern or structure. This ensures governance rules are technically enforced.

Run type-safe Showpad integrations with Pydantic AI.

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Connect Showpad MCP to Pydantic AI

Create your Vinkius account to connect Showpad to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Showpad with Pydantic AI

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Strict Asset Data Retrieval

The `get_asset_details` tool retrieves specific collateral data, and because of Pydantic validation, you know exactly what fields you're getting back. No unexpected fields or silent corruption. The agent uses this type safety when calling `search_assets`, guaranteeing that the search results structure is always correct for downstream processing.

Validated User and Org Data

Need to manage user data? The `list_users` tool gives a list, but `get_user_details` guarantees the output structure. If the underlying API changes, your agent fails loudly—you know something's wrong. This applies to organizational context too; whether you use `list_divisions` or `list_channels`, Pydantic ensures the resulting data model is validated every single time.

Complete Taxonomy Mapping

The system uses tools like `list_tags` to define content boundaries. Your agent can collect this tag list and then cross-reference it with asset IDs using `list_assets`. Everything is validated against a known schema. This systematic approach means that when your agent gathers information via `get_asset_details`, the metadata always conforms to what you expect, making the whole process reliable.

Setup guide

Set up Showpad 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": {
        "showpad-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Showpad MCP in Pydantic AI

The agent calls `search_assets` and immediately validates the output against a schema. This means you're never dealing with messy, unstructured search results; the data is always predictable.

You call `list_users` to get IDs. Then, using `get_user_details`, your agent gets the profile data. The validation layer confirms that every field—name, title, email—is present and correctly typed.

Nothing breaks silently. If the underlying API for `list_assets` suddenly returns an unexpected field or removes a required one, your agent fails immediately with a clear validation error. You're alerted to the issue right away.

Yes. The `list_tags` tool provides the list, and your agent can then validate that these tags follow a consistent naming pattern or structure. This ensures governance rules are technically enforced.

This MCP Server touches various types of structured metadata: content assets, user profiles, organizational divisions, and taxonomy tags. The runtime validation layer ensures every piece of this structural data is correct.

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