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 LangChain 10 tools — connect in under 2 minutes

Name: Avochato
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Avochato through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "avochato": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Avochato, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

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.

LangChain's ecosystem of 500+ components combines seamlessly with Avochato through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Avochato MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Avochato via MCP

Why Use LangChain with the Avochato MCP Server

LangChain provides unique advantages when paired with Avochato through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Avochato MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Avochato queries for multi-turn workflows

Avochato + LangChain Use Cases

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

RAG with live data: combine Avochato tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Avochato, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Avochato tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Avochato tool call, measure latency, and optimize your agent's performance

Avochato MCP Tools for LangChain (10)

These 10 tools become available when you connect Avochato to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Avochato + LangChain FAQ

Common questions about integrating Avochato MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.