How to Use the Avochato MCP in CrewAI

Q: How do I add Avochato tools to a CrewAI agent?

Pass the Vinkius URL directly into the agent's mcps list during initialization. For advanced setups, use MCPServerHTTP from the crewai.mcp package to filter which tools each agent can access.

Q: Do I need to write custom Python code to parse Avochato contacts?

No, the getcontact and listcontacts tools return structured data that the agents understand out of the box. The crew handles the raw JSON parsing internally, letting you focus on agent prompts.

Q: How safe is my customer contact list when using CrewAI?

All contact data fetched via listcontacts is processed in memory during the crew's execution. Vinkius runs the Avochato MCP Server in a zero-trust sandbox, ensuring your customer phone numbers and names are never leaked or stored.

Deploy autonomous agent crews using CrewAI to run your Avochato SMS support and marketing campaigns.

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Connect Avochato MCP to CrewAI

Create your Vinkius account to connect Avochato to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Avochato with CrewAI

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Coordinate multi-agent SMS campaigns using this MCP Server

This MCP Server lets your CrewAI agents collaborate on outgoing messaging campaigns using `create_broadcast` and `list_broadcasts`. A copywriter agent drafts the message, a compliance agent checks it, and an operations agent schedules the broadcast. By separating these tasks, you avoid the hallucinations common with single-agent setups. The entire crew shares memory, ensuring that the final SMS matches your brand guidelines before it goes out.

Build autonomous support crews that update CRM contacts

The `update_contact` tool enables your support agents to keep CRM profiles accurate based on incoming SMS conversations. While one agent analyzes customer sentiment from `list_messages`, another updates contact tags to reflect their current mood. If a customer asks to opt out, the agent immediately triggers `update_contact` to mark them as unsubscribed. This automated compliance loop runs 24/7 without requiring human intervention.

Verify inbox routing across specialized agent teams

The `who_am_i` tool allows your supervisor agent to route incoming tasks to the correct agent based on inbox ownership. If you manage multiple Avochato inboxes, the supervisor checks the current API user context before assigning support tickets. This prevents messages from getting crossed or sent from the wrong phone number. Your crew stays organized, ensuring that customer inquiries always land with the agent trained for that specific inbox.

Setup guide

Set up Avochato MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Avochato tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Avochato Analyst",
    goal="Access and analyze Avochato data via MCP.",
    backstory="Expert analyst with direct Avochato access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Avochato transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Avochato Analyst",
        goal="Access and analyze Avochato data via MCP.",
        backstory="Expert analyst with direct Avochato access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Avochato transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Avochato. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Avochato MCP in CrewAI

Pass the Vinkius URL directly into the agent's `mcps` list during initialization. For advanced setups, use `MCPServerHTTP` from the `crewai.mcp` package to filter which tools each agent can access.

Yes, CrewAI supports parallel tool execution. One agent can read history via `list_messages` while another uses `send_message` to reply, sharing the state through the crew's memory.

You can configure rate limits directly on your CrewAI agents. This prevents them from spamming `create_broadcast` or `send_message` and ensures your campaigns stay within Avochato's API limits.

No, the `get_contact` and `list_contacts` tools return structured data that the agents understand out of the box. The crew handles the raw JSON parsing internally, letting you focus on agent prompts.

All contact data fetched via `list_contacts` is processed in memory during the crew's execution. Vinkius runs the Avochato MCP Server in a zero-trust sandbox, ensuring your customer phone numbers and names are never leaked or stored.

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