Can the AI find an available slot for a specific service next Friday?

Yes. Upon providing the location and service ID along with the desired date, your agent invokes `get_availability`. The connector reads Picktime's master block array, isolating the open time windows seamlessly against existing rules (like business hours and buffers).

If a customer cancels on the phone, can the AI remove their booking?

Absolutely. Just provide the booking ID to the agent and it will utilize the `cancel_booking` function. Picktime will release the blocked slot immediately back to the customer-facing booking page.

Can I grab all upcoming appointments for a specific staff member?

Yes, by matching the staff member's ID from `list_staff` with the broader fetch generated by `list_bookings`. Alternatively, your agent can sort and filter the returned array natively in its reasoning stream, showing you only Dr. Silva's schedule.

Picktime MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Picktime
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Picktime through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Picktime "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Picktime?"
    )
    print(result.data)

asyncio.run(main())

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* 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 Picktime MCP Server

Connect your Picktime organization account to your AI agent and turn complex scheduling and availability management into a simple chat conversation.

Pydantic AI validates every Picktime tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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

Space & Resources — Easily retrieve structural logistics utilizing list_locations and inspect the service portfolio actively using list_services.
Staff Management — Gather team rosters through list_staff to orchestrate proper assignment mappings for upcoming reservations.
Booking Operations — Execute deep audits with list_bookings, review detailed entries (get_booking_details), and cleanly back out utilizing cancel_booking.
Availability Mapping — Audit live calendar empty spots using get_availability or check structured slots via list_classes for seamless planning.

The Picktime MCP Server exposes 10 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.

How to Connect Picktime to Pydantic AI via MCP

Follow these steps to integrate the Picktime MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Picktime with type-safe schemas

Why Use Pydantic AI with the Picktime MCP Server

Pydantic AI provides unique advantages when paired with Picktime 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 Picktime integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Picktime connection logic from agent behavior for testable, maintainable code

Picktime + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Picktime MCP Server delivers measurable value.

Type-safe data pipelines: query Picktime with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Picktime tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Picktime and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Picktime responses and write comprehensive agent tests

Picktime MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Picktime to Pydantic AI via MCP:

cancel_booking

Cancel a Picktime booking with a reason. The customer receives a cancellation notification and the time slot becomes available again for new bookings

get_availability

Get available booking time slots for a specific Picktime service on a given date. Returns free windows considering staff schedules, existing bookings, and buffer times. Essential for building custom booking flows

get_booking_details

Get full details of a specific Picktime booking including customer contact info, service booked, staff assigned, start/end times, payment status, and any customer notes

get_location

Used to resolve workspace boundaries before hitting schedules. Get detailed configuration for a specific Picktime location by ID. Returns location name, address, timezone, working hours, booking URL, and linked calendar/payment integrations

get_service_details

Get detailed configuration for a specific Picktime service. Returns name, duration, price, description, staff assignments, booking limits, and cancellation policy

list_bookings

List all bookings for a Picktime location with optional date filter. Returns customer names, booked services, staff assignments, times, statuses, and payment info. Essential for schedule management

list_classes

List all group classes configured for a Picktime location. Classes are multi-attendee bookings with capacity limits — yoga sessions, workshops, group trainings

list_locations

List all business locations configured in Picktime. Each location operates independently with its own services, staff, working hours, and booking pages. Multi-location businesses manage branches separately

list_services

List all bookable services for a Picktime location. Returns service names, durations, prices, descriptions, assigned staff, and buffer times. Services define what customers can book

list_staff

List all staff members at a Picktime location. Returns staff names, emails, roles, assigned services, working hours, and active status. Staff availability determines bookable time slots

Example Prompts for Picktime in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Picktime immediately.

"Find all of our active clinic locations in the Picktime registry."

"Cancel the booking record identified as BK123456."

"Can you check the availability data for 'Hair Styling' next Monday?"

Troubleshooting Picktime MCP Server with Pydantic AI

Common issues when connecting Picktime to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Picktime + Pydantic AI FAQ

Common questions about integrating Picktime MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Picktime MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.