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 LlamaIndex 10 tools — connect in under 2 minutes

Name: Avochato
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Avochato as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Avochato. "
            "You have 10 tools available."
        ),
    )

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

asyncio.run(main())

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* 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.

LlamaIndex agents combine Avochato tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

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

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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

Why Use LlamaIndex with the Avochato MCP Server

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

Data-first architecture: LlamaIndex agents combine Avochato tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Avochato tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Avochato, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Avochato tools were called, what data was returned, and how it influenced the final answer

Avochato + LlamaIndex Use Cases

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

Hybrid search: combine Avochato real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Avochato to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Avochato for fresh data

Analytical workflows: chain Avochato queries with LlamaIndex's data connectors to build multi-source analytical reports

Avochato MCP Tools for LlamaIndex (10)

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

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

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Avochato + LlamaIndex FAQ

Common questions about integrating Avochato MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Avochato tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.