# How to integrate Recruitee MCP with Pydantic AI ```json { "title": "How to integrate Recruitee MCP with Pydantic AI", "toolkit": "Recruitee", "toolkit_slug": "recruitee", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/recruitee/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/recruitee/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:23:33.477Z" } ``` ## Introduction This guide walks you through connecting Recruitee to Pydantic AI using the Composio tool router. By the end, you'll have a working Recruitee agent that can add a new candidate named alex lee, list all currently published job offers, get detailed profile for candidate emily chen through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Recruitee account through Composio's Recruitee MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Recruitee with - [OpenAI Agents SDK](https://composio.dev/toolkits/recruitee/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/recruitee/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/recruitee/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/recruitee/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/recruitee/framework/codex) - [OpenClaw](https://composio.dev/toolkits/recruitee/framework/openclaw) - [Hermes](https://composio.dev/toolkits/recruitee/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/recruitee/framework/cli) - [Google ADK](https://composio.dev/toolkits/recruitee/framework/google-adk) - [LangChain](https://composio.dev/toolkits/recruitee/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/recruitee/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/recruitee/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/recruitee/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/recruitee/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 Recruitee - 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 Recruitee 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 Recruitee MCP server, and what's possible with it? The Recruitee MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Recruitee account. It provides structured and secure access to your recruitment workflow, so your agent can perform actions like managing candidates, creating notes, publishing job offers, retrieving company info, and handling tags on your behalf. - Automated candidate management: Quickly create new candidate profiles, retrieve detailed information, or delete candidates as your hiring process evolves. - Collaborative note-taking: Let your agent add notes to candidate profiles, ensuring every piece of feedback or interview insight is captured and accessible. - Job offer publishing and retrieval: Effortlessly generate new job offers or fetch details on published positions from your public careers site. - Company and job listing access: Instantly get your company ID, list all candidates, or pull a list of current published job offers for reporting and coordination. - Tag and label management: Enable your agent to delete outdated tags, keeping your recruitment database organized and relevant. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `RECRUITEE_CREATE_CANDIDATE` | Create Candidate | Tool to create a new candidate profile. Use after gathering all candidate details. Example: "Create a new candidate named Jane Doe with email jane.doe@example.com." | | `RECRUITEE_CREATE_NOTE` | Create Note | Creates a new note for a candidate in Recruitee. Notes can be used to record interview feedback, assessments, or any observations about the candidate. Use this when you need to add commentary or documentation to a candidate's profile. | | `RECRUITEE_CREATE_OFFER` | Create Offer | Creates a new job offer or talent pool in Recruitee. Required fields include title, location IDs, and description. Use Get Locations action to retrieve valid location IDs before creating an offer. The offer status can be set to draft, internal, published, closed, or archived. | | `RECRUITEE_DELETE_CANDIDATE` | Delete Candidate | Tool to delete a candidate profile. Use when you need to permanently remove a candidate from your Recruitee account. Returns no content on success. | | `RECRUITEE_DELETE_TAG` | Delete Tag | Permanently deletes a tag from Recruitee by its ID. This action requires appropriate API permissions to delete tags. Use this when you need to remove unused or obsolete tags. Note: Deleting a tag removes it from all associated candidates and offers. | | `RECRUITEE_GET_CANDIDATE` | Get Candidate | Tool to retrieve detailed information about a specific candidate. Use when you need the candidate's full profile before proceeding. | | `RECRUITEE_GET_CANDIDATES` | Get Candidates | Tool to retrieve a list of all candidates in the company. Use when you need to fetch or filter candidates before proceeding. | | `RECRUITEE_GET_COMPANY_ID` | Get Company ID | Tool to retrieve the company ID of the authenticated account. Use when you need to confirm your company identity before other operations. | | `RECRUITEE_GET_COMPANY_OFFER_PUBLIC` | Get Company Offer Public | Tool to retrieve a specific published job offer by ID or slug from the public Careers Site API. Use after you have the offer identifier. | | `RECRUITEE_GET_DEPARTMENTS` | Get Departments | Tool to retrieve a list of company departments. Use when you need to reference or assign offers or candidates to departments. | | `RECRUITEE_GET_LOCATIONS` | Get Locations | Tool to retrieve a list of company locations. Use when you need to see all location options before assigning them to offers. | | `RECRUITEE_GET_NOTES` | Get Notes | Tool to retrieve a list of notes for a specific candidate. Use after confirming the candidate exists when you need to review their notes. | | `RECRUITEE_GET_OFFERS` | Get Offers | Tool to retrieve a list of all job offers. Use after authentication to browse or paginate your company's complete set of offers. | | `RECRUITEE_GET_PIPELINE_STAGES` | Get Pipeline Stages | Tool to retrieve pipeline stages of a job offer. Use when you have the offer ID and need its stages to track candidate progression. Example: "Get pipeline stages for offer ID 456." | | `RECRUITEE_GET_TAGS` | Get Tags | Retrieve all tags with optional filtering and pagination. Search by name, sort by name or usage count, and paginate through results. | | `RECRUITEE_LIST_EEO_JOB_CATEGORIES` | List EEO Job Categories | Tool to retrieve available EEO (Equal Employment Opportunity) job categories. Use when you need to see standard EEO job classification options. | | `RECRUITEE_LIST_INVOICES` | List Invoices | Tool to list invoices for a company. Use to retrieve billing invoice records. | | `RECRUITEE_LIST_LOCALIZATION_SETTINGS` | List Localization Settings | Tool to retrieve localization settings including proposed time format and start day of the week. Use when you need to check regional or time display preferences. | | `RECRUITEE_LIST_SHARE_COUNTRIES` | List Share Countries | Tool to retrieve all countries with region codes and phone codes per locale. Use when you need comprehensive country reference data including internationalization details. | | `RECRUITEE_LIST_SHARE_EEO_ANSWERS` | List Share EEO Answers | Tool to retrieve available EEO (Equal Employment Opportunity) answers. Use when you need to see available answer options for EEO compliance questions. | | `RECRUITEE_UPDATE_CANDIDATE` | Update Candidate | Updates an existing candidate's information in Recruitee. Use this to modify candidate details such as name, contact info, cover letter, tags, and social links. All fields except candidate_id are optional - only provide the fields you want to update. The API performs a partial update (PATCH), preserving any fields you don't specify. | | `RECRUITEE_UPDATE_NOTE` | Update Note | Tool to update an existing note for a candidate. Use when you need to modify note text or pin status after creation. | | `RECRUITEE_UPDATE_OFFER` | Update Offer | Updates an existing job offer or talent pool in Recruitee. Allows modification of offer details including title, description, requirements, status, locations, department assignment, work type (remote/hybrid/on-site), visibility settings, and application form field requirements. Only specified fields are updated; omitted fields remain unchanged. Requires the offer ID - use Get Offers or Get Offer actions to retrieve existing offer IDs. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Recruitee MCP server is an implementation of the Model Context Protocol that connects your AI agent to Recruitee. It provides structured and secure access so your agent can perform Recruitee 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 Recruitee - 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 Recruitee - MCPServerStreamableHTTP connects to the Recruitee 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 Recruitee 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 Recruitee composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["recruitee"], ) 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 Recruitee endpoint - The agent uses GPT-5 to interpret user commands and perform Recruitee operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent recruitee_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[recruitee_mcp], instructions=( "You are a Recruitee assistant. Use Recruitee 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 - Recruitee 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 Recruitee.\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 Recruitee composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["recruitee"], ) 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 recruitee_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[recruitee_mcp], instructions=( "You are a Recruitee assistant. Use Recruitee 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 Recruitee.\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 Recruitee through Composio's Tool Router. With this setup, your agent can perform real Recruitee 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 + Recruitee 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 Recruitee MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/recruitee/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/recruitee/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/recruitee/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/recruitee/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/recruitee/framework/codex) - [OpenClaw](https://composio.dev/toolkits/recruitee/framework/openclaw) - [Hermes](https://composio.dev/toolkits/recruitee/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/recruitee/framework/cli) - [Google ADK](https://composio.dev/toolkits/recruitee/framework/google-adk) - [LangChain](https://composio.dev/toolkits/recruitee/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/recruitee/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/recruitee/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/recruitee/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/recruitee/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. - [Connecteam](https://composio.dev/toolkits/connecteam) - Connecteam is a workforce management platform for deskless teams, streamlining operations, HR, and team communication. It helps businesses save time by automating scheduling, time tracking, and staff engagement tasks. - [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. - [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 Recruitee MCP? With a standalone Recruitee MCP server, the agents and LLMs can only access a fixed set of Recruitee tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Recruitee 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 Recruitee tools. ### Can I manage the permissions and scopes for Recruitee while using Tool Router? Yes, absolutely. You can configure which Recruitee 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 Recruitee data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)