How to Use the Castmagic MCP in Pydantic AI

Q: How do I integrate Castmagic into Pydantic AI?

You instantiate an MCPToolset with the server URL and pass it to your Agent. Pydantic AI then validates every tool response automatically.

Use Pydantic AI to enforce type-safe content repurposing with your MCP Server.

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Connect Castmagic MCP to Pydantic AI

Create your Vinkius account to connect Castmagic 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 Castmagic with Pydantic AI

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Perplexity

Validate transcript responses in Pydantic AI

Every response from `get_transcript_details` is checked against your models at runtime. If the API structure changes, your agent crashes safely instead of processing bad data. This ensures your content pipelines never break due to unexpected JSON schemas. You get total control over the data flow.

Query content with Pydantic AI

Fetch show notes and social posts using `get_magic_content` and cast them into your defined Python classes. It turns messy text into structured objects your app understands. Your agent logic stays consistent and type-checked. It makes handling dynamic content reliable for production apps.

List and manage media via MCP Server

Use `list_transcripts` to pull your history into a typed list. Your agent can iterate through these items safely to perform bulk content updates. It removes the risk of passing undefined data to your downstream functions. The type safety protects you from runtime errors.

Setup guide

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

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

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

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Common questions about Castmagic MCP in Pydantic AI

You instantiate an `MCPToolset` with the server URL and pass it to your Agent. Pydantic AI then validates every tool response automatically.

You get a type-safe interface for your content tools. If the server returns something weird, your agent catches it immediately.

Just define your Pydantic models to match the tool outputs. The integration handles the heavy lifting of validation.

Your agent receives a validation error. You can handle this gracefully in your code logic.

Your data is scoped to your account and encrypted. Only verified schema-compliant data is allowed into your agent's memory space.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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