# How to integrate Hunter MCP with Autogen

```json
{
  "title": "How to integrate Hunter MCP with Autogen",
  "toolkit": "Hunter",
  "toolkit_slug": "hunter",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/hunter/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/hunter/framework/autogen.md",
  "updated_at": "2026-05-12T10:15:24.853Z"
}
```

## Introduction

This guide walks you through connecting Hunter to AutoGen 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 AutoGen 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:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Hunter
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Hunter tools
- Run a live chat loop where you ask the agent to perform Hunter operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

## 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 agents and assistants directly to Hunter. Instead of manually wiring Hunter APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Hunter account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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 Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Hunter via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Hunter connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Hunter tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Hunter session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["hunter"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Hunter tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Hunter assistant agent with MCP tools
    agent = AssistantAgent(
        name="hunter_assistant",
        description="An AI assistant that helps with Hunter operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Hunter tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Hunter related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Hunter session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["hunter"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Hunter assistant agent with MCP tools
        agent = AssistantAgent(
            name="hunter_assistant",
            description="An AI assistant that helps with Hunter operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Hunter related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Hunter through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Hunter, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## 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

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- [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.
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- [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 Autogen?

Yes, you can. Autogen 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.

---
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