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 CrewAI 10 tools — connect in under 2 minutes

Name: Avochato
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Avochato through Vinkius, pass the Edge URL in the `mcps` parameter and every Avochato tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Avochato Specialist",
    goal="Help users interact with Avochato effectively",
    backstory=(
        "You are an expert at leveraging Avochato tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Avochato "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, Avochato becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Avochato tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Avochato

Why Use CrewAI with the Avochato MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Avochato through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Avochato + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Avochato for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Avochato, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Avochato tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Avochato against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Avochato MCP Tools for CrewAI (10)

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

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Avochato + CrewAI FAQ

Common questions about integrating Avochato MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.