How to Use the Typebot MCP in CrewAI

Q: How do I initiate a Typebot test flow with CrewAI?

You pass startchatsession to one of your agents. This lets the crew run through a simulated conversation, testing specific branches or interactions on the MCP Server.

Q: Can CrewAI list all existing Typebot instances?

Absolutely. The tool listtypebots allows any agent to fetch a comprehensive list of every conversational bot available for use in the crew's tasks.

Q: If I need details on one specific Typebot, which function do I call with CrewAI?

The gettypebotdetails tool provides all the necessary structural and logical information about a single bot. This is crucial for agents that need to understand how to interact with it.

Run autonomous Typebot operations with CrewAI’s specialized MCP Server tools.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Typebot MCP to CrewAI

Create your Vinkius account to connect Typebot 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.

GDPR Free for Subscribers

Setup Typebot with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Identify Bot Resources

A monitoring agent can use `list_workspaces` to get a full list of available environments. This initial step tells the crew which Typebot instances exist for research or action. The specialized agents then use this context to decide where they need to deploy effort, preventing unnecessary tool calls.

Analyze Conversation Results

When a bot finishes collecting data, an analyzing agent uses `list_typebot_results`. This action pulls collected user responses into the shared memory. The crew then uses this structured information to decide on escalation or follow-up actions. This ability to read and share lead data is key for complex, multi-step autonomous operations.

Manage Bot Lifecycle

Before an action agent can run, a moderator agent might first check the status using `get_typebot_details`. It also has the capability to call `delete_typebot` when resources need cleaning up. This keeps the entire MCP Server environment clean and predictable.

Setup guide

Set up Typebot 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 Typebot tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Typebot 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 Typebot. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Typebot now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Typebot MCP in CrewAI

You pass `start_chat_session` to one of your agents. This lets the crew run through a simulated conversation, testing specific branches or interactions on the MCP Server.

Absolutely. The tool `list_typebots` allows any agent to fetch a comprehensive list of every conversational bot available for use in the crew's tasks.

The `get_typebot_details` tool provides all the necessary structural and logical information about a single bot. This is crucial for agents that need to understand *how* to interact with it.

The server touches on metadata (workspaces, folders), live activity logs (chat sessions), and structured user responses. All these elements provide the context your crew needs to operate.

Your agents can manage the full lifecycle: they can list, get details for, publish changes (`publish_typebot`), and even delete entire bots through the MCP Server.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript