How to Use the Chameleon.io MCP in CrewAI

Q: How do I connect the Chameleon.io MCP Server to CrewAI?

Pass your Vinkius endpoint directly into the mcps array of your agent definition. The framework automatically parses the OpenAPI schema and binds the tools.

Q: How do I prevent a CrewAI agent from deleting Chameleon.io users?

Import MCPServerHTTP from crewai.mcp and apply a toolfilter. You explicitly allow reading functions while blocking destructive operations.

Deploy autonomous agent crews to manage Chameleon.io onboarding using CrewAI and this MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Chameleon.io MCP to CrewAI

Create your Vinkius account to connect Chameleon.io 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 Chameleon.io with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-Agent Chameleon.io Operations

Managing product adoption across thousands of accounts requires a team. You configure a CrewAI research agent with `list_experiences` to map out all active product tours. A secondary analyst agent then takes that map and evaluates completion rates. These agents share a memory pool during execution. When the first agent pulls data from this MCP Server, the subsequent agents already know the context. They work hierarchically to determine which onboarding flows need optimization.

Autonomous Survey Response Handling

Reading feedback manually wastes hours of product management time. You can assign `list_microsurvey_responses` to a dedicated monitoring agent. This agent wakes up on a schedule, pulls the latest text responses, and categorizes the sentiment. Escalation happens without human input. If the monitor detects angry feedback, it passes the user ID to an action agent. That agent executes `get_experience_details` to figure out exactly where the customer got stuck.

Coordinated Event Tracking

Keeping your adoption metrics accurate demands strict oversight. A moderator agent watches the session while a worker agent fires `track_user_event` for custom milestones. If the worker attempts to log malformed data, the moderator intercepts the call before it reaches the API. Python developers can restrict access easily. You use `MCPServerHTTP` with a `tool_filter` to ensure the worker only sees the tracking functions. It physically cannot call `delete_chameleon_user` because that tool gets hidden from its specific configuration.

Setup guide

Set up Chameleon.io 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 Chameleon.io tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your Vinkius endpoint directly into the `mcps` array of your agent definition. The framework automatically parses the OpenAPI schema and binds the tools.

Yes, you can assign different functions to different roles. One agent might handle `list_chameleon_events` while another exclusively runs identity updates.

Import `MCPServerHTTP` from `crewai.mcp` and apply a `tool_filter`. You explicitly allow reading functions while blocking destructive operations.

A manager agent can delegate tasks to workers equipped with these adoption tools. The manager reviews the survey analysis before deciding the next step.

Your tour configurations and user IDs live in an ephemeral sandbox that dies after the task completes. CrewAI only receives the strict JSON responses it requested from the MCP Server, keeping your core platform isolated.

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