Luma MCP Server for Pydantic AIGive Pydantic AI instant access to 6 tools to Add Guests To Event, Create Event, List Calendar Subscribers, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Luma through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Luma app connector for Pydantic AI is a standout in the Industry Titans category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Luma "
"(6 tools)."
),
)
result = await agent.run(
"What tools are available in Luma?"
)
print(result.data)
asyncio.run(main())
* 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 Luma MCP Server
Connect your Luma (lu.ma) account to any AI agent and take full control of your event orchestration and community engagement through natural conversation. Luma provides a robust platform for managing calendars and events, and this integration allows you to retrieve event metadata, manage guest lists, and create new activities directly from your chat interface.
Pydantic AI validates every Luma tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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
- Event & Calendar Orchestration — List all managed events and retrieve detailed metadata programmatically to ensure your community roadmap is always synchronized.
- Guest Lifecycle Management — Access and monitor guest lists and add new attendees directly from the AI interface to maintain high-fidelity event engagement.
- Communication & Update Control — List hosts and organizers linked to a calendar via natural language to drive better team alignment.
- Organization Oversight — Access organizational events and monitor system webhooks using simple AI commands.
- Operational Monitoring — Track system responses and manage event metadata to ensure your community workflows are always optimized.
The Luma MCP Server exposes 6 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.
All 6 Luma tools available for Pydantic AI
When Pydantic AI connects to Luma through Vinkius, your AI agent gets direct access to every tool listed below — spanning event-registration, community-engagement, attendee-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Manually add guests to an event
Create a new Luma event
List subscribers to your calendar
List guests for an event
List your Luma events
List all events in your organization
Connect Luma to Pydantic AI via MCP
Follow these steps to wire Luma into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Luma MCP Server
Pydantic AI provides unique advantages when paired with Luma 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 Luma integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Luma connection logic from agent behavior for testable, maintainable code
Luma + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Luma MCP Server delivers measurable value.
Type-safe data pipelines: query Luma with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Luma tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Luma and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Luma responses and write comprehensive agent tests
Example Prompts for Luma in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Luma immediately.
"List all my upcoming events in Luma."
"Show me the guest list for the 'Product Launch' event."
"Add 'sarah@example.com' to the workshop guest list."
Troubleshooting Luma MCP Server with Pydantic AI
Common issues when connecting Luma to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiLuma + Pydantic AI FAQ
Common questions about integrating Luma MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.