Loops MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Loops through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Loops "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Loops?"
)
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 Loops MCP Server
Loops is a modern email marketing and transactional email platform designed for startups and growing businesses. It provides powerful automation for email journeys, audience segmentation, contact management, and detailed analytics. This MCP server enables AI agents to manage contacts, mailing lists, trigger events for automated journeys, send transactional emails, and check suppression statuses — all through natural language commands.
Pydantic AI validates every Loops tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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.
Key capabilities:
- Search, create, update, and delete contacts
- Manage mailing lists
- Trigger email journeys with events
- Send transactional emails programmatically
- Check email suppression status
- View sent transactional email history
The Loops 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 Loops to Pydantic AI via MCP
Follow these steps to integrate the Loops 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 Loops with type-safe schemas
Why Use Pydantic AI with the Loops MCP Server
Pydantic AI provides unique advantages when paired with Loops 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 Loops integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Loops connection logic from agent behavior for testable, maintainable code
Loops + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Loops MCP Server delivers measurable value.
Type-safe data pipelines: query Loops with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Loops tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Loops and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Loops responses and write comprehensive agent tests
Loops MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Loops to Pydantic AI via MCP:
create_contact
Requires an email address. Optionally accepts firstName, lastName, and userGroup. Create a new contact in Loops
delete_contact
This action cannot be undone. Delete a contact from Loops by ID
find_contact
Returns the contact details if found. Find a contact in Loops by email address
get_contact_suppression
Suppressed emails will not receive emails. Returns the suppression status for the given email. Check if an email address is suppressed in Loops
list_mailing_lists
Use this to discover available lists for subscribing contacts. List all mailing lists in Loops
list_transactional_emails
Optionally accepts a limit parameter to control the number of results returned. List recently sent transactional emails from Loops
send_event
Requires an eventName. Optionally accepts email and/or userId to identify the recipient. Send an event to trigger email journeys in Loops
send_transactional_email
Requires the transactionalId. Optionally accepts email and dataVariables (as JSON string) for template variables. Send a transactional email via Loops
test_api_key
Returns success/failure status. Test if the Loops API key is valid and working
update_contact
Requires the contact ID. Accepts any fields to update such as firstName, lastName, email, userGroup, etc. Update an existing contact in Loops by ID
Example Prompts for Loops in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Loops immediately.
"Find the contact with email user@example.com in Loops"
"Create a new contact in Loops with email newuser@example.com, first name John, and last name Doe"
"List all mailing lists in my Loops account"
"Send a transactional email with template txn_123 to customer@example.com"
Troubleshooting Loops MCP Server with Pydantic AI
Common issues when connecting Loops to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiLoops + Pydantic AI FAQ
Common questions about integrating Loops 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Loops with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Loops to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.