How to Use the Chameleon.io MCP in Mastra AI

Q: How do I initialize the Chameleon.io tools in Mastra AI?

You instantiate a new MCPClient and pass your Vinkius server URL. Calling listTools() returns the array of Chameleon.io MCP Server functions. You spread those directly into your agent configuration.

Q: Can Mastra AI retry failed Chameleon.io event tracking?

The framework handles transient failures natively. If trackuserevent times out, the workflow engine applies exponential backoff and tries again automatically.

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Connect Chameleon.io MCP to Mastra AI

Create your Vinkius account to connect Chameleon.io to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Chameleon.io with Mastra AI

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Automate Chameleon.io Workflows

Handling product adoption requires logic that doesn't break when a network call drops. You pass `list_chameleon_events` into a Mastra AI agent to monitor what users are doing in your app. The framework automatically retries the fetch with exponential backoff if the API limits get hit. Branching logic takes over from there. If the agent sees a specific event, it can trigger `identify_chameleon_user` to update their profile properties. It then moves to the next step of the workflow without requiring human supervision.

Conditional Microsurvey Analysis

Raw feedback needs processing before it becomes useful. Your workflow can pull `list_microsurvey_responses` every morning to gather the previous day's NPS scores. If a score dips below your threshold, the agent branches off to alert the customer success team. Managing the underlying experience details happens in the same run. Calling `get_experience_details` lets the agent check if the associated tour is still active. The MCP Server handles the data extraction while Mastra manages the state.

Safe User Deletion Pipelines

Removing customer profiles is a high-stakes operation. You can wrap `delete_chameleon_user` in a Mastra workflow that requires human-in-the-loop approval. The agent stages the deletion, pauses execution, and waits for an admin to click approve. Deploying this setup takes one command. You configure the MCPClient with your Vinkius URL and spread `mcpClient.listTools()` into your agent's tool array. The entire compliance pipeline runs on your preferred cloud provider.

Setup guide

Set up Chameleon.io MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Chameleon.io tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "chameleonio-mcp-client",
  servers: {
    "chameleonio-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Chameleon.io Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Chameleon.io tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Chameleon.io transactions"
);
console.log(result.text);

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Common questions about Chameleon.io MCP in Mastra AI

You instantiate a new `MCPClient` and pass your Vinkius server URL. Calling `listTools()` returns the array of Chameleon.io MCP Server functions. You spread those directly into your agent configuration.

The framework handles transient failures natively. If `track_user_event` times out, the workflow engine applies exponential backoff and tries again automatically.

You create a workflow with conditional branches. Step one might run `list_user_segments` to find a cohort. Step two evaluates that data and decides whether to execute a follow-up action.

Mastra auto-detects the transport layer type. It connects to the Vinkius HTTP endpoint without manual transport configuration.

Vinkius processes your cohort lists inside a zero-trust V8 isolate. We manage the authentication tokens so your Mastra AI environment never exposes credentials in the local logs.

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