Where can I find my Loop API Token?

Go to your Loop Admin Portal, navigate to Settings > Manage API tokens, and generate a new token with Admin scopes.

Does this work with headless Shopify stores?

Yes, this server uses the Admin API, which manages the subscription data regardless of the storefront implementation.

Can I resume a subscription that was cancelled?

Generally, only 'Paused' subscriptions can be resumed. Cancelled subscriptions might need to be recreated depending on your Loop configuration.

Loop Subscriptions MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: Loop Subscriptions
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Loop Subscriptions 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 Loop Subscriptions "
            "(9 tools)."
        ),
    )

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

asyncio.run(main())

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About Loop Subscriptions MCP Server

Empower your AI agents to handle Loop Subscriptions directly. This server allows you to monitor and manage recurring revenue, customer profiles, and subscription lifecycles on Shopify.

Pydantic AI validates every Loop Subscriptions tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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

Subscription Control — List, inspect, pause, resume, or cancel subscriptions instantly
Order Orchestration — Monitor upcoming orders and skip next deliveries when requested by customers
Customer Management — Access detailed profiles and subscription history for your users
Operational Visibility — Track the status and health of your recurring business through simple natural language commands

The Loop Subscriptions MCP Server exposes 9 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 Loop Subscriptions to Pydantic AI via MCP

Follow these steps to integrate the Loop Subscriptions 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 9 tools from Loop Subscriptions with type-safe schemas

Why Use Pydantic AI with the Loop Subscriptions MCP Server

Pydantic AI provides unique advantages when paired with Loop Subscriptions 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 Loop Subscriptions integration code

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

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

Loop Subscriptions + Pydantic AI Use Cases

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

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

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

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

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

Loop Subscriptions MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect Loop Subscriptions to Pydantic AI via MCP:

cancel_subscription

Optional reason can be provided. Cancel a subscription

get_customer

Get customer details

get_subscription

Get detailed info for a single subscription

list_customers

List all customers with active or past subscriptions

list_orders

List subscription orders

list_subscriptions

List all Loop Subscriptions

pause_subscription

You can optionally provide a resume date. Pause an active subscription

resume_subscription

Resume a paused subscription

skip_next_order

Skip the next scheduled order

Example Prompts for Loop Subscriptions in Pydantic AI

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

"List my active subscriptions."

"Pause subscription #12345 until 2026-12-01."

"Skip the next delivery for customer 'John Doe'."

Troubleshooting Loop Subscriptions MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Loop Subscriptions + Pydantic AI FAQ

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