How to Use the Hunter MCP in AutoGen

Q: Is it possible to track Hunter credit usage across AutoGen agents?

You can assign a management agent to monitor getaccountusage. It can stop the other agents from making calls if they hit your defined credit limit.

Debate your sales strategy with AutoGen. Use these Hunter tools to let your agents negotiate lead quality and outreach targets.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Hunter MCP to AutoGen

Create your Vinkius account to connect Hunter to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Hunter with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Negotiate lead quality between agents

Set a research agent to call `search_domain_emails` and a validation agent to call `verify_email_address`. They can debate the viability of each lead before creating a record. This creates a system of checks and balances. Your agents ensure that only high-quality contacts reach your CRM, reducing your bounce rate effectively.

Deliberate on domain outreach

Use `get_domain_email_count` to inform your agents about the scale of a potential target. Your agents discuss whether the volume justifies the outreach effort. This consensus-driven approach prevents wasted time on low-yield domains. Your agents agree on the best strategy before they take any action in your account.

Manage CRM records collaboratively

Assign one agent to `create_new_lead` and another to `update_lead_info` based on incoming intelligence. They negotiate the state of your leads to ensure data consistency. This keeps your CRM records accurate without human input. Your agents coordinate the updates, ensuring that every lead record reflects the latest information.

Setup guide

Set up Hunter MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Hunter tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Hunter_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Hunter data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

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

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Hunter_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Hunter data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Hunter. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Hunter now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Hunter MCP in AutoGen

You pass the tools to your AssistantAgent constructor. The adapter automatically handles the schema conversion so your agents can start debating tool calls immediately.

Yes. You can build a system where one agent proposes a lead and another evaluates it using `verify_email_address`. They reach a consensus before acting.

You can assign a management agent to monitor `get_account_usage`. It can stop the other agents from making calls if they hit your defined credit limit.

The agents use the tool descriptions to understand their capabilities. They decide which tool fits the current part of their conversation and invoke it accordingly.

The server manages your credentials securely. Your agents receive only the necessary tool access, and your API key never leaves the secure MCP environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript