Can the AI automatically send an SMS to a new contact?

Yes! Use the `send_message` tool. You'll need to provide the phone number and the message body. Your agent will instantly transmit the SMS through your Avochato inbox.

How do I find all contacts that have been tagged with a specific label?

Simply ask the agent to run the `get_contacts` tool with the target tag. It will return a list of matching contact profiles, including their names and phone numbers.

Does the integration allow for sending images through MMS?

Yes. The `send_message` tool supports a `media_url` parameter, allowing you to include images or other media files in your outgoing messages.

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

Name: Avochato
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 Avochato 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 Avochato "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

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IAMAccess control

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DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Avochato MCP Server

Connect your Avochato account to any AI agent and manage your business messaging workflows through natural conversation.

Pydantic AI validates every Avochato 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.

What you can do

Business Messaging — Send and receive SMS/MMS messages with full delivery status tracking and conversation history
Contact Organization — Create, update, and search for contacts and manage tags to segment your audience
Broadcast Management — Coordinate and audit mass messaging campaigns and broadcasts across your target inboxes
Inbox Auditing — Monitor specific subdomains and verify current API user details for secure communication

The Avochato 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 Avochato to Pydantic AI via MCP

Follow these steps to integrate the Avochato 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 Avochato with type-safe schemas

Why Use Pydantic AI with the Avochato MCP Server

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

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

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

Avochato + Pydantic AI Use Cases

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

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

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

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

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

Avochato MCP Tools for Pydantic AI (10)

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

create_broadcast

Schedule or send a message broadcast

create_contact

Add a new contact to Avochato

get_account_check

Verify Avochato account connection

get_contact

Get details for a specific contact

list_broadcasts

List message broadcasts

list_contacts

List and search contacts

list_messages

List message history in Avochato

send_message

Send an SMS/MMS message

update_contact

Update an existing contact

who_am_i

Get current API user and inbox information

Example Prompts for Avochato in Pydantic AI

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

"Send a message to '555-0199': 'Hi there, your order is ready for pickup!'"

"List the last 10 messages from today."

"Find all contacts with the tag 'High-Value'."

Troubleshooting Avochato MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Avochato + Pydantic AI FAQ

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