# How to integrate Re amaze MCP with Mastra AI

```json
{
  "title": "How to integrate Re amaze MCP with Mastra AI",
  "toolkit": "Re amaze",
  "toolkit_slug": "re_amaze",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/re_amaze/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/re_amaze/framework/mastra-ai.md",
  "updated_at": "2026-05-12T10:23:25.810Z"
}
```

## Introduction

This guide walks you through connecting Re amaze to Mastra AI using the Composio tool router. By the end, you'll have a working Re amaze agent that can list all tags used in recent reports, show most popular response templates for support, analyze tag trends from last week's conversations through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a Re amaze account through Composio's Re amaze MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Re amaze with

- [OpenAI Agents SDK](https://composio.dev/toolkits/re_amaze/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/re_amaze/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/re_amaze/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/re_amaze/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/re_amaze/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/re_amaze/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/re_amaze/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/re_amaze/framework/cli)
- [Google ADK](https://composio.dev/toolkits/re_amaze/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/re_amaze/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/re_amaze/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/re_amaze/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/re_amaze/framework/crew-ai)

## 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 Re amaze tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Re amaze 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 Re amaze 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 Re amaze MCP server, and what's possible with it?

The Re amaze MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Re:amaze account. It provides structured and secure access to your customer support environment, so your agent can retrieve report tags, access canned response templates, and streamline support workflows for your team.
- Tag usage analytics: Instantly pull all tags used in reports so your agent can analyze conversation trends, monitor support topics, or generate insights about ticket categorization.
- Effortless response template retrieval: Fetch your brand's pre-built response templates, making it easy for the agent to suggest or automate consistent replies across channels.
- Streamlined reply suggestions: Quickly surface relevant canned responses for agents or bots to use, speeding up customer replies and ensuring brand consistency.
- Support workflow automation: Leverage tags and templates to help your agent automate repetitive customer support tasks and standardize communication processes.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `RE_AMAZE_GET_REPORTS_TAGS` | Get report tags | Tool to retrieve a list of tags used in reports. Use when analyzing tag usage metrics across conversations. |
| `RE_AMAZE_GET_RESPONSE_TEMPLATES` | Get Response Templates | Tool to retrieve response templates for the brand. Use when you need canned responses to streamline replies. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Re amaze MCP server is an implementation of the Model Context Protocol that connects your AI agent to Re amaze. It provides structured and secure access so your agent can perform Re amaze operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 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

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Re amaze through MCP.

### 2. Install dependencies

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

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

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
```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,
});
```

### 5. Create a Tool Router session for Re amaze

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "re_amaze" for Re amaze access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["re_amaze"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Re amaze MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

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 Re amaze toolkit
```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);
```

### 7. Create the Mastra agent

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

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Re amaze 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
```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: {
        re_amaze: 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);
});
```

## Complete Code

```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: ["re_amaze"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "re_amaze-mastra-agent",
    instructions: "You are an AI agent with Re amaze 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: { re_amaze: 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 Re amaze 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

## How to build Re amaze MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/re_amaze/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/re_amaze/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/re_amaze/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/re_amaze/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/re_amaze/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/re_amaze/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/re_amaze/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/re_amaze/framework/cli)
- [Google ADK](https://composio.dev/toolkits/re_amaze/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/re_amaze/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/re_amaze/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/re_amaze/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/re_amaze/framework/crew-ai)

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- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Re amaze MCP?

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

### Can I use Tool Router MCP with Mastra AI?

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 Re amaze tools.

### Can I manage the permissions and scopes for Re amaze while using Tool Router?

Yes, absolutely. You can configure which Re amaze 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.

### How safe is my data with Composio Tool Router?

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 Re amaze data and credentials are handled as safely as possible.

---
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