How to Use the CHATFLY MCP in CrewAI

Q: How do I add the CHATFLY MCP Server to a CrewAI agent?

You can pass the Vinkius URL directly into the agent's mcps parameter during initialization. For more control, use MCPServerHTTP from the crewai.mcp package and apply a tool filter to only expose tools like sendbotmessage.

Q: How do CrewAI agents share CHATFLY conversation histories?

CrewAI's built-in memory system allows tools like getconversationhistory to store context. Once one agent retrieves the chat history, that data is accessible to all other agents in the crew.

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Connect CHATFLY MCP to CrewAI

Create your Vinkius account to connect CHATFLY 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 CHATFLY with CrewAI

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Deploy specialized support squads with CrewAI

The `list_fly_conversations` tool feeds live chat logs to your CrewAI supervisor agent for real-time monitoring. Your supervisor agent can watch active chats and hand off complex cases to human support. Meanwhile, a technical writer agent uses `list_uploaded_documents` to verify training data and triggers updates when necessary.

Sync shared memory across support agents

The `get_conversation_history` tool supplies past customer interactions directly to your CrewAI shared memory bank. This shared memory prevents agents from repeating questions. If a bot response is needed, the designated writer agent calls `send_bot_message` with the complete historical context already loaded.

Manage CHATFLY bots autonomously using this MCP Server

The `list_chatfly_bots` tool lets your CrewAI manager agent audit all active customer service bots in your account. The agent queries this MCP integration to fetch configurations via `get_chatbot_details` and identify which bots need retraining. If a bot is outdated, the crew coordinates to run `trigger_bot_training` and monitors the training status. You get a self-managing support ecosystem that optimizes its own performance.

Setup guide

Set up CHATFLY 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 CHATFLY tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You can pass the Vinkius URL directly into the agent's `mcps` parameter during initialization. For more control, use `MCPServerHTTP` from the `crewai.mcp` package and apply a tool filter to only expose tools like `send_bot_message`.

Yes, CrewAI's hierarchical process allows a manager agent to delegate tasks. One agent can analyze documents using `list_uploaded_documents`, while another agent executes `trigger_bot_training` based on those findings.

CrewAI's built-in memory system allows tools like `get_conversation_history` to store context. Once one agent retrieves the chat history, that data is accessible to all other agents in the crew.

CrewAI supports stdio, SSE, and Streamable HTTP transports. When connecting to Vinkius, the library handles the underlying HTTP connection so your agents can focus on executing tasks.

All data processed by this MCP Server, including bot details from `get_chatbot_details` and chat history, runs in an ephemeral, zero-trust sandbox. Credentials are never written to disk, keeping your support logs and system settings secure.

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