How to integrate Repairshopr MCP with Mastra AI

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Introduction

This guide walks you through connecting Repairshopr to Mastra AI using the Composio tool router. By the end, you'll have a working Repairshopr agent that can list all upcoming appointments for today, fetch all assets linked to a customer, show attachments for a specific service case, delete an invoice by its unique id through natural language commands.

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

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

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 Repairshopr tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Repairshopr 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 Repairshopr 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 Repairshopr MCP server, and what's possible with it?

The Repairshopr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Repairshopr account. It provides structured and secure access to your repair shop management system, so your agent can perform actions like managing customer records, handling appointments, viewing assets, retrieving attachments, and organizing contacts on your behalf.

  • Effortless appointment management: Instantly retrieve details of specific appointments, get upcoming schedules, or delete canceled slots directly through your agent.
  • Comprehensive customer and contact handling: Let your agent fetch lists of customers or contacts, update records, or permanently remove outdated customer information for streamlined CRM workflows.
  • Asset tracking and lookup: Quickly search for assets, confirm asset details, or filter assets by customer or status, making it easy to keep tabs on all equipment under management.
  • Service case and attachment retrieval: Have your agent pull all attachments linked to a specific service case, ensuring quick access to important files and documentation.
  • Estimate and invoice cleanup: Empower your agent to delete estimates or invoices that are no longer needed, helping you maintain a tidy, organized business record system.

Supported Tools & Triggers

Tools
Delete AppointmentTool to delete a specific appointment by its id.
Delete CustomerTool to delete a specific customer by id.
Delete EstimateTool to delete a specific estimate by id.
Delete InvoiceTool to delete a specific invoice by id.
Get AppointmentTool to retrieve details of a specific appointment by its id.
Get AppointmentsTool to retrieve a list of appointments.
Get AssetTool to retrieve details of a specific asset by its id.
Get AssetsTool to retrieve a paginated list of assets.
Get Case AttachmentsTool to retrieve attachments for a specific service case.
Get ContactsTool to retrieve a paginated list of contacts.
Get CustomerTool to retrieve details of a specific customer by id.
Get CustomersTool to retrieve a list of customers.
Get Employee Time ClockTool to retrieve the last time clock entry for a specific user.
Get EstimateTool to retrieve details of a specific estimate by id.
Get EstimatesTool to retrieve a list of estimates.
Get InvoiceTool to retrieve details of a specific invoice by id.
Get InvoicesTool to retrieve a paginated list of invoices.
Get LeadTool to retrieve details of a specific lead by its id.
Get LeadsTool to retrieve a paginated list of leads.
Get PaymentTool to retrieve details of a specific payment by id.
Get PaymentsTool to retrieve a paginated list of payments.
Get ProductTool to retrieve details of a specific product by id.
Get ProductsTool to retrieve a list of products.
Get Products By CategoryTool to retrieve products filtered by category id.
Get Product CategoriesTool to retrieve product categories.
Get Product SerialsTool to retrieve all serial numbers for a specific product.
Get TicketTool to retrieve details of a specific ticket by its id.
Get UserTool to retrieve details of a specific user by id.
Get UsersTool to retrieve a list of all users.
Create AppointmentTool to create a new appointment.
Create AssetTool to create a new asset.
Create CustomerTool to create a new customer.
Create EstimateTool to create a new estimate.
Create InvoiceTool to create a new invoice.
Create LeadTool to create a new lead.
Create PaymentTool to create a new payment.
Create ProductTool to create a new product in inventory.
Add Product PhotoTool to add photo(s) to a specific product.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

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

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 Repairshopr through MCP.

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

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

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

Create a Tool Router session for Repairshopr

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

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

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 Repairshopr toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "repairshopr-mastra-agent",
    instructions: "You are an AI agent with Repairshopr 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

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: {
        repairshopr: 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 Repairshopr 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 Repairshopr 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: ["repairshopr"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "repairshopr-mastra-agent",
    instructions: "You are an AI agent with Repairshopr 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: { repairshopr: 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 Repairshopr 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 Repairshopr MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Repairshopr MCP?

With a standalone Repairshopr MCP server, the agents and LLMs can only access a fixed set of Repairshopr tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Repairshopr 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 Repairshopr tools.

Can I manage the permissions and scopes for Repairshopr while using Tool Router?

Yes, absolutely. You can configure which Repairshopr 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 Repairshopr data and credentials are handled as safely as possible.

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