# How to integrate Connecteam MCP with Pydantic AI ```json { "title": "How to integrate Connecteam MCP with Pydantic AI", "toolkit": "Connecteam", "toolkit_slug": "connecteam", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/connecteam/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/connecteam/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:07:22.192Z" } ``` ## Introduction This guide walks you through connecting Connecteam to Pydantic 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 Pydantic 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) - [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 your Composio API key and User ID - How to create a Composio Tool Router session for Connecteam - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Connecteam workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 with an active API key - Basic familiarity with Python and async programming ### 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 Install the required libraries. What's happening: - composio connects your agent to external SaaS tools like Connecteam - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Connecteam - MCPServerStreamableHTTP connects to the Connecteam MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session 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 session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Connecteam composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["connecteam"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Connecteam endpoint - The agent uses GPT-5 to interpret user commands and perform Connecteam operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent connecteam_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[connecteam_mcp], instructions=( "You are a Connecteam assistant. Use Connecteam tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Connecteam API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Connecteam.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Connecteam composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["connecteam"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent connecteam_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[connecteam_mcp], instructions=( "You are a Connecteam assistant. Use Connecteam tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Connecteam.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Connecteam through Composio's Tool Router. With this setup, your agent can perform real Connecteam actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Connecteam for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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) - [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 Pydantic AI? Yes, you can. Pydantic 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)