# How to integrate Connecteam MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Connecteam MCP with Vercel AI SDK v6", "toolkit": "Connecteam", "toolkit_slug": "connecteam", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/connecteam/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/connecteam/framework/ai-sdk.md", "updated_at": "2026-05-12T10:07:22.192Z" } ``` ## Introduction This guide walks you through connecting Connecteam to Vercel AI SDK v6 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 Vercel AI SDK 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) - [Mastra AI](https://composio.dev/toolkits/connecteam/framework/mastra-ai) - [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: - How to set up and configure a Vercel AI SDK agent with Connecteam integration - Using Composio's Tool Router to dynamically load and access Connecteam tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## 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 you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 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'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) 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, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Connecteam tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Connecteam-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["connecteam"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Connecteam tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to connecteam, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Connecteam tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript 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({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); 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 { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) 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, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["connecteam"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to connecteam, like summarize my last 5 emails, send an email, etc... :)))\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({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Connecteam agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-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) - [Mastra AI](https://composio.dev/toolkits/connecteam/framework/mastra-ai) - [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 Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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)