# How to integrate Connecteam MCP with Mastra AI

```json
{
  "title": "How to integrate Connecteam MCP with Mastra AI",
  "toolkit": "Connecteam",
  "toolkit_slug": "connecteam",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/connecteam/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/connecteam/framework/mastra-ai.md",
  "updated_at": "2026-05-12T10:07:22.192Z"
}
```

## 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 archive users who have left the company, create new staff accounts for onboarding, list all available time-off policy types 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.

## Also integrate Connecteam with

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CONNECTEAM_ARCHIVE_USERS` | Archive Users | Tool to archive one or more users by their unique IDs. Use when you need to deactivate users without deleting their records. |
| `CONNECTEAM_CREATE_USERS` | Create Users | Tool to create multiple users in Connecteam. Use when you need to add several staff or admin accounts at once. |
| `CONNECTEAM_GENERATE_UPLOAD_URL` | Generate Upload URL | Tool to generate a pre-signed URL for uploading a file. Use when you need a secure, time-limited URL prior to file upload. |
| `CONNECTEAM_GET_CHAT` | Get Chat | Tool to retrieve chat conversations. Use when you need to list all team chats/channels after confirming your Communications hub is on Expert plan. |
| `CONNECTEAM_GET_CUSTOM_FIELD_CATEGORIES` | Get Custom Field Categories | Tool to retrieve all custom field categories. Use when you need to list or filter custom field categories in your Connecteam account. |
| `CONNECTEAM_GET_CUSTOM_FIELDS` | Get Custom Fields | Tool to retrieve all custom fields associated with the account. Use when you need to filter, sort, or page through custom fields after authentication. |
| `CONNECTEAM_GET_FORMS` | Get Forms | Tool to retrieve all form definitions from Connecteam. Use when you need to list all existing forms after enabling the Forms API. |
| `CONNECTEAM_GET_JOBS` | Get Jobs | Tool to retrieve a list of job objects relevant to a specific instance ID. Use after confirming scheduler or time clock instance ID when you need to filter and page through jobs. |
| `CONNECTEAM_GET_PERFORMANCE_INDICATORS` | Get Performance Indicators | Tool to retrieve the list of performance metric indicators. Use when you need to list available performance indicators for data analysis. Examples: "List performance metrics". |
| `CONNECTEAM_GET_POLICY_TYPES` | Get Policy Types | Tool to retrieve available time-off policy types. Use before filtering or creating time-off requests by policyTypeId. |
| `CONNECTEAM_GET_PUBLISHERS` | Get Publishers | Tool to retrieve a list of all custom publishers. Use when you need to list custom publishers after confirming API access. |
| `CONNECTEAM_GET_SCHEDULERS` | Get Schedulers | Tool to retrieve a list of job schedulers associated with the account. Use after authentication when you need to enumerate all schedulers. |
| `CONNECTEAM_GET_SMART_GROUPS` | Get Smart Groups | Tool to retrieve all smart groups associated with the account. Use when you need to list all smart groups after authenticating with a valid API key. |
| `CONNECTEAM_GET_TASK_BOARDS` | Get Task Boards | Tool to retrieve all task boards. Use after authenticating with a valid API key to list available task boards. |
| `CONNECTEAM_GET_USERS` | Get Users | Tool to retrieve a list of all users associated with your account. Use when you need to fetch and filter user data. |
| `CONNECTEAM_LIST_ME` | List Me | Tool to retrieve account information including company name and company ID. Use when you need to get details about the authenticated account. |

## Supported Triggers

None listed.

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

The Connecteam MCP server is an implementation of the Model Context Protocol that connects your AI agent to Connecteam. It provides structured and secure access so your agent can perform Connecteam 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 Connecteam 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 Connecteam

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
```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);
```

### 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 Connecteam 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: "connecteam-mastra-agent",
    instructions: "You are an AI agent with Connecteam 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 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
```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);
});
```

## 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: ["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

## How to build Connecteam MCP Agent with another framework

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

## Related Toolkits

- [Ashby](https://composio.dev/toolkits/ashby) - Ashby is an applicant tracking system that handles job postings, candidate management, and hiring analytics.
- [Async interview](https://composio.dev/toolkits/async_interview) - Async interview is an on-demand video interview platform for streamlined hiring. Candidates record responses on their schedule, so employers can review anytime.
- [Bamboohr](https://composio.dev/toolkits/bamboohr) - BambooHR is a cloud-based HR management platform for small and mid-sized businesses. It streamlines employee data, HR workflows, and reporting in one easy interface.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Lever](https://composio.dev/toolkits/lever) - Lever is an applicant tracking system that blends sourcing, CRM, and analytics for recruiting. It helps companies scale hiring with collaborative workflows and actionable insights.
- [Recruitee](https://composio.dev/toolkits/recruitee) - Recruitee is collaborative hiring software that centralizes recruitment tasks for teams. It streamlines sourcing, interviewing, and hiring so you can fill roles faster.
- [Remote retrieval](https://composio.dev/toolkits/remote_retrieval) - Remote retrieval is a logistics automation tool for managing laptop and monitor returns. It streamlines return tracking, saving time and hassle for IT and ops teams.
- [Sap successfactors](https://composio.dev/toolkits/sap_successfactors) - Sap successfactors is a cloud-based human capital management suite for HR, payroll, recruiting, and talent management. It helps organizations centralize employee data and streamline the entire employee lifecycle.
- [Talenthr](https://composio.dev/toolkits/talenthr) - TalentHR is an intuitive, all-in-one HR tool for managing employee records, leave, and HR workflows. It streamlines HR operations so businesses can focus on people, not paperwork.
- [Workable](https://composio.dev/toolkits/workable) - Workable is an all-in-one HR software platform that streamlines hiring, employee management, and payroll. It helps teams simplify recruiting, onboarding, and staff operations in one place.
- [Workday](https://composio.dev/toolkits/workday) - Workday is a cloud-based ERP platform for HR, finance, and workforce analytics. It streamlines employee management, payroll, and business operations in a single system.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.
- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

## Frequently Asked Questions

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

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.

### 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 Connecteam tools.

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

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.

### 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 Connecteam data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)