How to integrate Chameleon MCP with Mastra AI

This guide walks you through connecting Chameleon to Mastra AI using the Composio tool router. By the end, you'll have a working Chameleon agent that can search your customer records, count customers, review experiences, inspect analytics, and track deliveries through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Chameleon account through Composio's Chameleon MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Chameleon is a product adoption platform for building in-app experiences, managing customer data, and analyzing user engagement. It helps teams improve onboarding, feature discovery, and product adoption with targeted user experiences.

14 Tools

Introduction

This guide walks you through connecting Chameleon to Mastra AI using the Composio tool router. By the end, you'll have a working Chameleon agent that can search your customer records, count customers, review experiences, inspect analytics, and track deliveries through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Chameleon account through Composio's Chameleon MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Chameleon with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKLlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Chameleon tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Chameleon tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Chameleon agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Chameleon MCP server, and what's possible with it?

The Chameleon MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Chameleon account. It provides structured and secure access to your in-app experiences, customer records, delivery activity, and engagement data, so your agent can review experiences, analyze engagement, find or update customer records, track customer events, and inspect deliveries on your behalf.

  • Experience discovery and review: Have your agent list and review tours, microsurveys, launchers, embeds, and tooltips without changing or publishing them.
  • Engagement and response analysis: Let the agent examine tour interactions and microsurvey responses to understand how customers engage with your experiences.
  • Customer record management: Direct your agent to find, count, create, or update customer profiles and companies using external references and structured criteria.
  • Customer event tracking: Instruct your agent to record named events for customer profiles, such as completing onboarding or activating a feature.
  • Delivery and account oversight: Have your agent review scheduled experience deliveries, change history, configured domains or environments, and targeting metadata such as segments, tags, themes, events, and properties.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Chameleon through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Chameleon

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["chameleon"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Chameleon MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "chameleon" for Chameleon access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Chameleon toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "chameleon-mastra-agent",
    instructions: "You are an AI agent with Chameleon tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        chameleon: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Chameleon toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Chameleon and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["chameleon"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      chameleon: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "chameleon-mastra-agent",
    instructions: "You are an AI agent with Chameleon tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { chameleon: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Chameleon through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows
TOOLS

Supported Tools

Every Chameleon action and event your agent gets out of the box.

Count Customer Records

Count Chameleon profiles or companies matching structured filters without retrieving the matching records.

Get Account Identity

Return the Chameleon account ID and admin user ID associated with the connected Account Secret.

Get Delivery

Retrieve one Chameleon experience delivery by ID without triggering, changing, or cancelling it.

Get Experience

Retrieve one Chameleon tour, microsurvey, launcher, embed, or tooltip by ID without modifying or publishing it.

List Changes

List one page of Chameleon change history across the account or for one supported experience.

List Deliveries

List one page of scheduled Chameleon experience deliveries, optionally filtered by experience or profile, without triggering a new delivery.

List Domains or Environments

List one page of configured Chameleon domains or environments without changing account routing configuration.

List Experience Analytics

List one page of tour interactions or microsurvey responses for a specific Chameleon experience.

List Experiences

List one page of Chameleon tours, microsurveys, launchers, embeds, or tooltips without modifying or publishing them.

List Targeting Metadata

List one page of Chameleon segments, tags, themes, tracked event names, or profile/company property definitions used to interpret targeting and analytics data.

Lookup Customer Record

Retrieve one Chameleon profile or company by its Chameleon ID or external identifier.

Search Customer Records

Search Chameleon profiles or companies with structured filters and return one offset-paginated page of matching records.

Track Event

Irreversibly record one named event for a Chameleon profile identified by ID or external UID; provide exactly one identifier.

Upsert Customer Record

Create or update one Chameleon profile or company by external UID and return its Chameleon ID.

FRAMEWORKS

How to build Chameleon MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Chameleon MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Chameleon MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Chameleon MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Chameleon MCP with Claude Cowork

Codex logo

Codex

Use Chameleon MCP with Codex

OpenClaw logo

OpenClaw

Use Chameleon MCP with OpenClaw

Hermes logo

Hermes

Use Chameleon MCP with Hermes

CLI logo

CLI

Use Chameleon MCP with CLI

Google ADK logo

Google ADK

Use Chameleon MCP with Google ADK

LangChain logo

LangChain

Use Chameleon MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Chameleon MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Chameleon MCP with LlamaIndex

CrewAI logo

CrewAI

Use Chameleon MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Chameleon MCP server, the agents and LLMs can only access a fixed set of Chameleon tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Chameleon and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Mastra AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Chameleon tools.

Yes, absolutely. You can configure which Chameleon scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Chameleon data and credentials are handled as safely as possible.

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