Can I see how many users completed a specific tour?

Yes! Use the `get_experience_details` tool with the tour's unique ID. The agent will return engagement metrics including completion counts and active status.

How do I identify a user to start showing them tours?

Use the `identify_chameleon_user` tool. Provide a unique user ID and any relevant custom properties. This allows Chameleon to target that user with the appropriate segments and experiences.

Where do I find my Chameleon Account Secret?

Log in to your Chameleon Dashboard, navigate to 'Settings' in the sidebar, and then select 'API'. You can view and copy your Account Secret from there.

Chameleon.io MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Chameleon.io
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Chameleon.io through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Chameleon.io "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Chameleon.io?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Chameleon.io MCP Server

Connect your Chameleon.io account to any AI agent and take full control of your user onboarding and product adoption experiences through natural conversation. Streamline how you guide and engage your users.

Pydantic AI validates every Chameleon.io tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Experience Oversight — List and retrieve details for all Chameleon tours, launchers, and microsurveys natively
User Segmentation — Access and monitor your configured user segments to understand targeting flawlessly
Response Auditing — Retrieve and analyze recent microsurvey responses to gather user feedback securely
User Intelligence — Identify and update user profiles with custom properties in real-time
Behavioral Tracking — Log and monitor custom user events to trigger the right experience at the right time flawlessly
Compliance Management — Handle data deletion requests by removing user records directly within your workspace

The Chameleon.io MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Chameleon.io to Pydantic AI via MCP

Follow these steps to integrate the Chameleon.io MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Chameleon.io with type-safe schemas

Why Use Pydantic AI with the Chameleon.io MCP Server

Pydantic AI provides unique advantages when paired with Chameleon.io through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Chameleon.io integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Chameleon.io connection logic from agent behavior for testable, maintainable code

Chameleon.io + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Chameleon.io MCP Server delivers measurable value.

Type-safe data pipelines: query Chameleon.io with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Chameleon.io tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Chameleon.io and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Chameleon.io responses and write comprehensive agent tests

Chameleon.io MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Chameleon.io to Pydantic AI via MCP:

delete_chameleon_user

Permanently delete a user and their data from Chameleon

get_experience_details

Get details for a specific experience

identify_chameleon_user

Identify or update a user in Chameleon

list_chameleon_events

List recent events tracked by Chameleon

list_experiences

List all Chameleon experiences (Tours, Launchers, Microsurveys)

list_microsurvey_responses

List recent responses to microsurveys

list_user_segments

List all configured user segments

track_user_event

Track a custom event for a specific user

Example Prompts for Chameleon.io in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Chameleon.io immediately.

"List all my active Chameleon experiences."

"Identify user 'user_999' with plan: 'enterprise' and industry: 'fintech'."

"Track a 'checkout_completed' event for user 'user_123'."

Troubleshooting Chameleon.io MCP Server with Pydantic AI

Common issues when connecting Chameleon.io to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Chameleon.io + Pydantic AI FAQ

Common questions about integrating Chameleon.io MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Chameleon.io MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.