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How to integrate Connecteam MCP with Mastra AI

Connect Mastra AI to Connecteam MCP. Archive users who have left the company, create new staff accounts for onboarding, and more using natural language, with authentication handled for you.

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Connecteam

Api Key

Connecteam is a workforce management platform for deskless teams, streamlining operations, HR, and team communication. It helps businesses save time by automating scheduling, time tracking, and staff engagement tasks.

35 Tools

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Introduction

This guide walks you through connecting Connecteam to Mastra AI using the Composio tool router. By the end, you'll have a working Connecteam agent that can create and archive users, list jobs and schedulers, browse forms and task boards, view chats, and check smart groups through natural language commands.

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

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

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Connecteam with

Claude Code Claude Cowork OpenAI Agents SDK Claude Agent SDK Codex OpenClaw Hermes Atomic Agent Google ADK LangChain Vercel AI SDK LlamaIndex CrewAI Pydantic AI AutoGen

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

The Connecteam MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Connecteam account. It provides structured and secure access to your workforce management data, so your agent can perform actions like managing users, retrieving chats, processing forms, handling jobs, and analyzing performance metrics on your behalf.

User management and automation: Quickly add new employees, archive inactive users, or update user details to keep your workforce roster up to date.
Team communications monitoring: Retrieve chat conversations and team channels, making it easy for your agent to help you stay on top of internal messages and updates.
Form and workflow processing: List and review all existing forms, so your agent can help automate routine HR tasks and data collection.
Job and scheduling insights: Access job objects tied to your schedules or time clocks, letting your agent assist with workforce planning and role assignments.
Performance and policy analytics: Fetch performance indicators and available time-off policy types, enabling your agent to surface key metrics and streamline HR policy management.

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:

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

Step-by-step Guide

Step by step09 STEPS

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 Connecteam 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 Connecteam

typescript

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

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

What's happening:

create spins up a short-lived MCP HTTP endpoint for this user
The toolkits array contains "connecteam" for Connecteam 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 Connecteam toolkit

Create the Mastra agent

typescript

const agent = new Agent({
    name: "connecteam-mastra-agent",
    instructions: "You are an AI agent with Connecteam 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: {
        connecteam: 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 Connecteam 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 Connecteam 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: ["connecteam"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "connecteam-mastra-agent",
    instructions: "You are an AI agent with Connecteam 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: { connecteam: 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 Connecteam 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 Connecteam action and event your agent gets out of the box.

Archive Users

Tool to archive one or more users by their unique IDs.

Create Daily Note

Create a daily note for qualified users or groups.

Create Jobs

Create parent jobs or add sub-jobs beneath existing parent jobs.

Create Shifts

Create shifts without notifications by default.

Create Time Activities

Create shifts or breaks, optionally splitting existing shifts around breaks.

Create Users

Tool to create multiple users in Connecteam.

Delete Geofence

Delete one geofence and automatically verify its absence.

Delete Job

Delete a standalone job by ID.

Delete Shift

Delete one shift from a scheduler.

Delete Time Activity

Delete one shift or manual-break activity from a time clock.

Generate Upload URL

Tool to generate a pre-signed URL for uploading a file.

Get Chat

Retrieve a page of chat conversations, including team chats and channels.

Get Custom Field Categories

Tool to retrieve all custom field categories.

Get Custom Fields

Retrieve custom fields associated with the account, with options to filter, sort, and page through results.

Get Forms

Tool to retrieve all form definitions from Connecteam.

Get Form Submissions

Retrieve submissions for a form, optionally filtered by user or submit time.

Get Geofences

List all geofences configured for a time clock.

Get Jobs

Tool to retrieve a list of job objects relevant to a specific instance ID.

Get Pay Rates

Retrieve effective user pay rates over a required date range.

Get Performance Indicators

Tool to retrieve the list of performance metric indicators.

Get Policy Balances

Retrieve a page of user balances for a time-off policy type.

Get Policy Types

Tool to retrieve available time-off policy types.

Get Publishers

Retrieve a page of custom publishers associated with the account.

Get Schedulers

Tool to retrieve a list of job schedulers associated with the account.

Get Shifts

List shifts in a scheduler for a required Unix-time window.

Get Smart Groups

Tool to retrieve all smart groups associated with the account.

Get Task Boards

Tool to retrieve all task boards.

Get Time Activities

Retrieve shifts, manual breaks, and time off grouped by user.

Get Time Off Requests

Retrieve time-off requests overlapping a required date range.

Get Timesheet Totals

Retrieve payroll-oriented total hours for one time clock.

Get Users

Retrieve and filter a page of users associated with the account.

List Me

Tool to retrieve account information including company name and company ID.

Update Job

Update a standalone job or sub-job by ID.

Update Shifts

Update shifts; notifyUsers defaults true and may notify users for published shifts.

Update Users

Update up to 25 users, identifying every item by user ID or phone number.

FRAMEWORKS

How to build Connecteam MCP Agent with another framework

Claude Code

Use Connecteam MCP with Claude Code

Claude Cowork

Use Connecteam MCP with Claude Cowork

OpenAI Agents SDK

Use Connecteam MCP with OpenAI Agents SDK

Claude Agent SDK

Use Connecteam MCP with Claude Agent SDK

Codex

Use Connecteam MCP with Codex

OpenClaw

Use Connecteam MCP with OpenClaw

Hermes

Use Connecteam MCP with Hermes

Atomic Agent

Use Connecteam MCP with Atomic Agent

Google ADK

Use Connecteam MCP with Google ADK

LangChain

Use Connecteam MCP with LangChain

Vercel AI SDK

Use Connecteam MCP with Vercel AI SDK

LlamaIndex

Use Connecteam MCP with LlamaIndex

CrewAI

Use Connecteam MCP with CrewAI

Pydantic AI

Use Connecteam MCP with Pydantic AI

AutoGen

Use Connecteam MCP with AutoGen

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Ashby

Api Key

Ashby is an applicant tracking system that handles job postings, candidate management, and hiring analytics.

7shifts

Api Key

7shifts is a restaurant team management platform for scheduling, time clocks, payroll, and team communication. It helps operators keep labor, shifts, and staff workflows organized in one place.

AI Ark

Api Key

AI Ark is a people and company intelligence platform with search, enrichment, and recruiting APIs. It helps teams find accurate contact data and discover hiring insights faster.

Async interview

Api Key

Async interview is an on-demand video interview platform for streamlined hiring. Candidates record responses on their schedule, so employers can review anytime.

FAQ

Frequently asked questions

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

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

Start with Connecteam.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Connecteam tool your agent needs.Free to start.

Start building

How to integrate Connecteam MCP with Mastra AI

Connect Connecteam without auth hassles

Introduction

Also integrate Connecteam with

TL;DR

What is Mastra AI?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import libraries and validate environment

Create a Tool Router session for Connecteam

Configure Mastra MCP client and fetch tools

Create the Mastra agent

Set up interactive chat interface

Complete Code

Conclusion

Supported Tools

How to build Connecteam MCP Agent with another framework

Claude Code

Claude Cowork

OpenAI Agents SDK

Claude Agent SDK

Codex

OpenClaw

Hermes

Atomic Agent

Google ADK

LangChain

Vercel AI SDK

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Ashby

7shifts

AI Ark

Async interview

Frequently asked questions

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

Can I use Tool Router MCP with Mastra AI?

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

How safe is my data with Composio Tool Router?

Start with Connecteam.It takes 30 seconds.