How to Use the Corsizio MCP in Pydantic AI
Get type-safe access to Corsizio attendee profiles, payments, and event stats using validated models in Pydantic AI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Corsizio MCP to Pydantic AI
Create your Vinkius account to connect Corsizio 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.
Type-Safe Corsizio Operations via MCP Server
The `get_attendee_details` tool fetches registration profiles, payment histories, and event boundaries for any registered user. Because you are using Pydantic AI, the incoming JSON payload is validated against strict schemas before your agent even sees it. This prevents runtime errors caused by missing fields or unexpected data formats. If an attendee record has an empty email field, the framework catches it immediately, so you don't end up with broken records.
Track Event Schedules and Capacities
The `get_event_details` tool retrieves the exact setup, pricing structure, and registration limits for any class. Your agent uses this data to answer user questions about seat availability or ticket pricing. Combine this with `list_events` to build an automated monitoring script. The script checks which workshops are nearing capacity and alerts your team to open new sessions.
Reconcile Payments and Refunds
The `list_payments` tool resolves transaction IDs, payment amounts, and currencies across your entire account. Your agent can cross-reference these records with external bookkeeping systems to automate financial reporting. When handling disputes, the agent uses `list_refunds` to check if a transaction was already reversed. This keeps your refund process transparent and prevents double-refunding customer accounts.
Set up Corsizio 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 deprecatedMCPServerHTTPclass with full protocol support. - 2
Configure the FastMCPToolset
Pass a JSON-style config dict to
FastMCPToolsetwith 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 callagent.run(). Swapopenai:gpt-4ofor any supported model — Anthropic, Google, Mistral, or Groq.
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset
toolset = FastMCPToolset({
"mcpServers": {
"corsizio-mcp": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
})
agent = Agent(
"openai:gpt-4o",
toolsets=[toolset],
system_prompt="You have access to Corsizio tools.",
)
result = await agent.run("List recent Corsizio transactions")
print(result.output) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Corsizio. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Corsizio MCP in Pydantic AI
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