# How to integrate Hunter MCP with Pydantic AI ```json { "title": "How to integrate Hunter MCP with Pydantic AI", "toolkit": "Hunter", "toolkit_slug": "hunter", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/hunter/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/hunter/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:15:24.853Z" } ``` ## Introduction This guide walks you through connecting Hunter to Pydantic AI using the Composio tool router. By the end, you'll have a working Hunter agent that can find all public emails at acme.com, enrich company details for tesla.com, create new lead with given info through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Hunter account through Composio's Hunter MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Hunter with - [OpenAI Agents SDK](https://composio.dev/toolkits/hunter/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/hunter/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/hunter/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/hunter/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/hunter/framework/codex) - [OpenClaw](https://composio.dev/toolkits/hunter/framework/openclaw) - [Hermes](https://composio.dev/toolkits/hunter/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/hunter/framework/cli) - [Google ADK](https://composio.dev/toolkits/hunter/framework/google-adk) - [LangChain](https://composio.dev/toolkits/hunter/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/hunter/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/hunter/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/hunter/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/hunter/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 Hunter - 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 Hunter 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 Hunter MCP server, and what's possible with it? The Hunter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Hunter account. It provides structured and secure access to your lead generation and enrichment tools, so your agent can perform actions like finding emails, enriching company data, managing leads, and organizing leads lists on your behalf. - Email discovery and search: Instantly ask your agent to find all public email addresses for a given company or domain, complete with metadata to fuel your outreach and marketing campaigns. - Smart lead creation and management: Let your agent add new leads, update lead details, or delete outdated entries to keep your Hunter account organized and up-to-date. - Company and contact enrichment: Have the agent fetch detailed company profiles or use the Email Finder to infer the best contact email for a specific person at a target company. - Leads list organization: Direct your agent to create, update, or remove custom leads lists—making it easy to segment prospects for personalized marketing or sales workflows. - Custom attribute management: Empower your agent to create or delete custom lead attributes, tailoring your CRM data fields to match your unique business needs. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `HUNTER_ACCOUNT_INFORMATION` | Account Information | Tool to retrieve information about your Hunter account. Use when you need to check your plan details and usage limits after confirming credentials. Returns `searches.available` and `verifications.available` fields among others; check these before bulk operations to avoid quota exhaustion. | | `HUNTER_COMBINED_ENRICHMENT` | Combined Enrichment | Tool to find both person and company information from an email address or LinkedIn handle in a single request. Use when you need complete professional profile enrichment including employment and company details. | | `HUNTER_COMPANY_ENRICHMENT` | Company Enrichment | Tool to get enrichment information for a company by its domain. Use when you need full company details (industry, description, location, metrics) from Hunter. | | `HUNTER_CREATE_CUSTOM_ATTRIBUTE` | Create custom lead attribute | Tool to create a new custom lead attribute in your account. Use after deciding on the attribute label. | | `HUNTER_CREATE_LEAD` | Create Lead | Tool to create a new lead. Use after gathering all prospect details to save them to your Hunter account. | | `HUNTER_CREATE_LEADS_LIST` | Create Leads List | Tool to create a new leads list. Use when you need to organize leads into a custom list before adding leads. | | `HUNTER_DELETE_CUSTOM_ATTRIBUTE` | Delete Custom Attribute | Tool to delete an existing custom attribute. Use after confirming the attribute ID to be removed. | | `HUNTER_DELETE_LEAD` | Delete Lead | Tool to delete a lead. Use after confirming the lead's ID to remove it from your Hunter.io account. | | `HUNTER_DELETE_LEADS_LIST` | Delete Leads List | Tool to delete a leads list by its ID. Use after confirming the leads list ID to remove it from your Hunter.io account. | | `HUNTER_DISCOVER_COMPANIES` | Discover Companies | Tool to search and retrieve companies matching specified criteria using filters or natural language queries. Use when you need to discover companies from Hunter's B2B dataset based on industry, location, size, or other characteristics. | | `HUNTER_DOMAIN_SEARCH` | Domain Search | Tool to search all email addresses for a given domain or company. Use when you need public emails and metadata for outreach or enrichment. Rate-limited; HTTP 429 returned on excess requests — honor the Retry-After header. | | `HUNTER_EMAIL_COUNT` | Email Count | Tool to get the total number of email addresses Hunter has for a domain or company with breakdowns by type, department, and seniority. Use when you need email volume statistics without consuming API credits (this call is free). | | `HUNTER_EMAIL_FINDER` | Email Finder | Tool to find the most likely email address for a person at a domain or company. Use when you have a person's name and a domain or company and need to infer their email. Results include a confidence score and status; treat emails with status 'accept_all' or 'risky' as lower reliability. Each call consumes API credits — avoid re-enriching the same contact. | | `HUNTER_EMAIL_VERIFIER` | Email Verifier | Tool to verify the deliverability of an email address. Use when you need to ensure an address is valid and reachable. Response may include statuses `accept_all` or `risky`, indicating uncertain deliverability; do not treat these as fully valid without explicit review. For bulk verification, honor `Retry-After` headers on HTTP 429 responses and use exponential backoff. | | `HUNTER_GET_CUSTOM_ATTRIBUTE` | Get Custom Attribute | Tool to retrieve details of a specific custom attribute. Use when you need the label and slug for an attribute ID. | | `HUNTER_GET_LEAD` | Get Lead | Tool to retrieve details of a specific lead by ID. Use after confirming the lead's ID to fetch its full record. | | `HUNTER_GET_LEADS_LIST` | Get Leads List | Tool to retrieve details of a specific leads list by ID. Use when you need to inspect the contents of an existing leads list. | | `HUNTER_LIST_CAMPAIGNS` | List Campaigns | Tool to get all email campaigns in your Hunter account. Campaigns are returned in reverse-chronological order by creation date. Use when you need to retrieve and filter campaigns by status (started/archived) with pagination support. | | `HUNTER_LIST_CUSTOM_ATTRIBUTES` | List Custom Attributes | Tool to list all custom lead attributes in your account. Use when you need to retrieve your account's custom lead attributes after authenticating. | | `HUNTER_LIST_LEADS` | List Leads | Tool to list all leads saved in your account with optional filters. Use when you need to retrieve leads with specific criteria after confirming your API key. | | `HUNTER_LIST_LEADS_LISTS` | List Leads Lists | Tool to list all leads lists in your account. Use when you need to retrieve and paginate through your leads lists. | | `HUNTER_PEOPLE_ENRICHMENT` | People Enrichment | Tool to find all information associated with an email address or LinkedIn profile including name, location, job title and social handles. Use when you need to enrich contact data with additional personal and professional details. | | `HUNTER_UPDATE_CUSTOM_ATTRIBUTE` | Update Custom Attribute | Tool to update an existing custom attribute's label. Use when renaming a custom attribute after creation. | | `HUNTER_UPDATE_LEAD` | Update Lead | Tool to update details of an existing lead by ID. Use when you need to modify saved lead attributes after creation. | | `HUNTER_UPDATE_LEADS_LIST` | Update Leads List | Tool to update the name of a specific leads list. Use when renaming an existing leads list. | | `HUNTER_UPSERT_LEAD` | Upsert Lead | Tool to create or update a lead by email in one call. Use when you want to ensure a lead exists with the provided information without checking its existence first. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Hunter MCP server is an implementation of the Model Context Protocol that connects your AI agent to Hunter. It provides structured and secure access so your agent can perform Hunter 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 Hunter - 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 Hunter - MCPServerStreamableHTTP connects to the Hunter 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 Hunter 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 Hunter composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["hunter"], ) 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 Hunter endpoint - The agent uses GPT-5 to interpret user commands and perform Hunter operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent hunter_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[hunter_mcp], instructions=( "You are a Hunter assistant. Use Hunter 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 - Hunter 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 Hunter.\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 Hunter composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["hunter"], ) 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 hunter_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[hunter_mcp], instructions=( "You are a Hunter assistant. Use Hunter 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 Hunter.\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 Hunter through Composio's Tool Router. With this setup, your agent can perform real Hunter 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 + Hunter 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 Hunter MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/hunter/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/hunter/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/hunter/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/hunter/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/hunter/framework/codex) - [OpenClaw](https://composio.dev/toolkits/hunter/framework/openclaw) - [Hermes](https://composio.dev/toolkits/hunter/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/hunter/framework/cli) - [Google ADK](https://composio.dev/toolkits/hunter/framework/google-adk) - [LangChain](https://composio.dev/toolkits/hunter/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/hunter/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/hunter/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/hunter/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/hunter/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Hunter MCP? With a standalone Hunter MCP server, the agents and LLMs can only access a fixed set of Hunter tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Hunter 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 Hunter tools. ### Can I manage the permissions and scopes for Hunter while using Tool Router? Yes, absolutely. You can configure which Hunter 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 Hunter data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)