Can I create a new work shift through the agent?

Yes. Use the `create_shift` tool and provide the employee ID, start/end times, and location ID. Your agent will add the shift to the 7shifts schedule immediately.

How do I list all restaurant locations?

Use the `list_locations` tool. Your agent will retrieve all restaurant locations, departments, and roles configured in your 7shifts account.

Can I see who is currently requesting time off?

Absolutely. Use the `list_time_off` tool to retrieve all pending and approved time-off requests from your staff for auditing purposes.

7shifts MCP Server for Pydantic AI 6 tools — connect in under 2 minutes

Name: 7shifts
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 6 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect 7shifts through 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 7shifts "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in 7shifts?"
    )
    print(result.data)

asyncio.run(main())

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About 7shifts MCP Server

Connect your 7shifts account to your AI agent to streamline restaurant workforce management. From creating weekly schedules to auditing employee time-off requests, your agent handles staffing operations through natural conversation.

Pydantic AI validates every 7shifts 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

Employee Management — List all staff members, create new profiles, and manage employee technical details
Scheduling & Shifts — Create, view, and update work shifts for your entire team across different locations
Time-Off Requests — Audit pending or approved time-off and submit new requests on behalf of employees
Labor Tracking — Access time punch data and monitor clock-in/out patterns for payroll accuracy
Location Organization — Manage multiple restaurant locations, departments, and roles seamlessly

The 7shifts 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.

How to Connect 7shifts to Pydantic AI via MCP

Follow these steps to integrate the 7shifts 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 6 tools from 7shifts with type-safe schemas

Why Use Pydantic AI with the 7shifts MCP Server

Pydantic AI provides unique advantages when paired with 7shifts 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 7shifts integration code

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

Dependency injection system cleanly separates your 7shifts connection logic from agent behavior for testable, maintainable code

7shifts + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the 7shifts MCP Server delivers measurable value.

Type-safe data pipelines: query 7shifts with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple 7shifts tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query 7shifts and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock 7shifts responses and write comprehensive agent tests

7shifts MCP Tools for Pydantic AI (6)

These 6 tools become available when you connect 7shifts to Pydantic AI via MCP:

create_employee

Requires name and email. Create a new staff profile inside 7shifts with basic contact information

create_shift

Requires user_id, location_id, and ISO 8601 start/end times. Assign a new work shift to a 7shifts employee for a specific date and time

list_employees

Retrieve all employees registered in the 7shifts company account

list_locations

Retrieve all locations, departments, and roles configured in the 7shifts account

list_shifts

Retrieve scheduled work shifts from 7shifts, filterable by date or location

list_time_off

Retrieve pending or approved employee time-off requests from 7shifts

Example Prompts for 7shifts in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with 7shifts immediately.

"List all employees for my restaurant."

"Create a shift for employee 456 on Dec 20th from 9 AM to 5 PM at location 123."

"Are there any pending time-off requests?"

Troubleshooting 7shifts MCP Server with Pydantic AI

Common issues when connecting 7shifts to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

7shifts + Pydantic AI FAQ

Common questions about integrating 7shifts 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 7shifts MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.