How to Use the Chaport MCP in CrewAI

Deploy a team of CrewAI agents to manage your Chaport inbox. Automate visitor research, triage chats, and draft responses autonomously.

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Connect Chaport MCP to CrewAI

Create your Vinkius account to connect Chaport 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 Chaport with CrewAI

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Perplexity

Assign specialized agents to support

One bot trying to manage your Chaport inbox usually fails. CrewAI lets you build a dedicated support squad where each agent has a specific job. A researcher agent constantly polls `list_website_visitors` to identify who is currently browsing. Targets get analyzed instantly. A separate analyst agent runs `get_visitor_details`. The team builds a complete profile of the customer before they even type their first question.

Triage complex chats with this MCP Server

Senior Chaport operators shouldn't waste time on password resets. Your triage agent monitors incoming requests by executing `get_visitor_last_chat`. It reads the context and decides if the issue requires human intervention. Simple Chaport inquiries get immediate answers. A responder agent fires back a reply using `send_agent_message`. For difficult cases, the crew alerts an available staff member after checking `list_online_agents`.

Audit team performance autonomously

Quality assurance for Chaport chats takes hours of manual transcript reading. You can deploy a supervisor agent to review resolved tickets by calling `get_chat_history`. It grades the interaction based on your company guidelines. Accountability happens automatically. The supervisor pulls roster data via `list_chaport_operators` and maps these reviews to specific staff members. Management gets a daily performance report without lifting a finger.

Setup guide

Set up Chaport 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 Chaport tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Chaport 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="Chaport Analyst",
        goal="Access and analyze Chaport data via MCP.",
        backstory="Expert analyst with direct Chaport access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Chaport 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 Chaport. 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 Chaport MCP in CrewAI

Install the required tools package. Pass the Vinkius MCP Server URL directly into the connection array when defining your agent.

Yes. You assign the MCP Server connection to specific roles. The researcher gets read-only access while the responder agent handles the actual messaging.

Use the HTTP class from the framework and apply a tool filter. This prevents your analysis agent from accidentally calling `send_agent_message` through the MCP Server during a review task.

The framework natively supports stdio, SSE, and Streamable HTTP. Just drop in the endpoint URL and the system negotiates the connection automatically.

Authentication is handled entirely through a single secure token. Whenever your crew pulls sensitive contact details or chat transcripts, the transaction occurs in an isolated, temporary environment that leaves no trace behind.

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