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 LangChain 8 tools — connect in under 2 minutes

Name: Chameleon.io
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Chameleon.io through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "chameleonio": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Chameleon.io, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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High SecurityEnterprise-grade

IAMAccess control

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DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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.

LangChain's ecosystem of 500+ components combines seamlessly with Chameleon.io through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Chameleon.io via MCP

Why Use LangChain with the Chameleon.io MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Chameleon.io MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Chameleon.io queries for multi-turn workflows

Chameleon.io + LangChain Use Cases

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

RAG with live data: combine Chameleon.io tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Chameleon.io, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Chameleon.io tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Chameleon.io tool call, measure latency, and optimize your agent's performance

Chameleon.io MCP Tools for LangChain (8)

These 8 tools become available when you connect Chameleon.io to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Chameleon.io + LangChain FAQ

Common questions about integrating Chameleon.io MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.