# How to integrate Connecteam MCP with CrewAI ```json { "title": "How to integrate Connecteam MCP with CrewAI", "toolkit": "Connecteam", "toolkit_slug": "connecteam", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/connecteam/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/connecteam/framework/crew-ai.md", "updated_at": "2026-05-12T10:07:22.192Z" } ``` ## Introduction This guide walks you through connecting Connecteam to CrewAI 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 CrewAI 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) - [Mastra AI](https://composio.dev/toolkits/connecteam/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/connecteam/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Connecteam connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Connecteam - Build a conversational loop where your agent can execute Connecteam operations ## What is CrewAI? CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews. Key features include: - Agent Roles: Define specialized agents with specific goals and backstories - Task Management: Create tasks with clear descriptions and expected outputs - Crew Orchestration: Combine agents and tasks into collaborative workflows - MCP Integration: Connect to external tools through Model Context Protocol ## 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: - Python 3.9 or higher - A Composio account and API key - A Connecteam connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 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 dependencies **What's happening:** - composio connects your agent to Connecteam via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates with Composio - USER_ID scopes the session to your account - OPENAI_API_KEY lets CrewAI use your chosen OpenAI model ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **What's happening:** - CrewAI classes define agents and tasks, and run the workflow - MCPServerHTTP connects the agent to an MCP endpoint - Composio will give you a short lived Connecteam MCP URL ```python import os from composio import Composio from crewai import Agent, Task, Crew from crewai_tools import MCPServerAdapter import dotenv dotenv.load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") ``` ### 5. Create a Composio Tool Router session for Connecteam **What's happening:** - You create a Connecteam only session through Composio - Composio returns an MCP HTTP URL that exposes Connecteam tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["connecteam"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **What's Happening:** - Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication. - MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format. - Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools. - Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops. - Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries. ```python server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users search the internet effectively", backstory="You are a helpful assistant with access to search tools.", tools=tools, verbose=False, max_iter=10, ) ``` ### 7. Create a CLI Chatloop and define the Crew **What's Happening:** - Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable. - Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean. - Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses. - Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context. - Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response. - Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity. ```python print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Complete Code ```python from crewai import Agent, Task, Crew, LLM from crewai_tools import MCPServerAdapter from composio import Composio from dotenv import load_dotenv import os load_dotenv() GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not GOOGLE_API_KEY: raise ValueError("GOOGLE_API_KEY is not set in the environment.") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment.") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment.") # Initialize Composio and create a session composio = Composio(api_key=COMPOSIO_API_KEY) session = composio.create( user_id=COMPOSIO_USER_ID, toolkits=["connecteam"], ) url = session.mcp.url # Configure LLM llm = LLM( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY"), ) server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users with internet searches", backstory="You are an expert assistant with access to Composio Search tools.", tools=tools, llm=llm, verbose=False, max_iter=10, ) print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Conclusion You now have a CrewAI agent connected to Connecteam through Composio's Tool Router. The agent can perform Connecteam operations through natural language commands. Next steps: - Add role-specific instructions to customize agent behavior - Plug in more toolkits for multi-app workflows - Chain tasks for complex multi-step operations ## 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) - [Mastra AI](https://composio.dev/toolkits/connecteam/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/connecteam/framework/llama-index) ## 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 CrewAI? Yes, you can. CrewAI 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)