How to Use the FindThatLead MCP in OpenAI Agents SDK

Q: How do I connect FindThatLead to the OpenAI Agents SDK?

Install the package with pip install openai-agents and configure the HTTP streamable server parameters. Pass the server instance inside the mcpservers list when initializing your Agent to auto-discover all 12 tools instantly.

Q: Can my agent verify email lists using FindThatLead and OpenAI Agents SDK?

Yes, your agent can call emailverifier to check the validity of any email address. You can set up a specialized agent to loop through lists returned by listleads and clean them before execution.

Q: How does caching work with FindThatLead on the OpenAI Agents SDK?

Set cacheToolsList=True in your configuration to cache the tool definitions. This prevents the SDK from querying the MCP Server on every single turn, reducing latency during high-volume prospecting runs.

Q: What happens when a search returns no emails?

The emailfinder tool returns a clean null or empty response when no match exists. Your agent detects this and can automatically switch to domainsearch to find alternative contacts at the same company.

Build production-grade agents that find and verify prospect emails using the FindThatLead MCP Server and OpenAI Agents SDK.

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Connect FindThatLead MCP to OpenAI Agents SDK

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

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Setup FindThatLead with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Target domain lookups with automated guardrails

The `domain_search` tool queries the target domain to find active business email addresses directly from your Python agent. This tool returns structured lead data that your agent parses to identify key decision-makers without manual scraping. Your agent can immediately pass these emails to `email_verifier` to filter out dead addresses before they hit your CRM. OpenAI tracing monitors this workflow, letting you verify that your agent handles rate limits and API quotas correctly.

Track outbound campaign performance in production

The `get_campaign` tool pulls live metrics from your active email campaigns directly into your agent's context. Your agent uses this data to check reply rates and bounce metrics, adjusting follow-up sequences based on real-world performance. By using `list_campaigns`, your specialized routing agent can hand off low-performing campaigns to a copywriter agent. This multi-agent setup keeps your pipeline moving without manual intervention.

Scale local outreach with OpenAI Agents SDK and MCP

The `local_prospector` tool finds local business leads within specified geographic parameters to build targeted outbound lists. It extracts raw local business data so your agent can qualify prospects based on location and industry. Once qualified, the agent runs `create_lead` to save the contact details directly to your account. This prevents duplicate records and ensures your outbound sales reps only contact fresh, validated leads.

Setup guide

Set up FindThatLead MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all FindThatLead tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives FindThatLead tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate FindThatLead tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="FindThatLead Agent",
            instructions="You have access to FindThatLead tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about FindThatLead MCP in OpenAI Agents SDK

Install the package with `pip install openai-agents` and configure the HTTP streamable server parameters. Pass the server instance inside the `mcp_servers` list when initializing your Agent to auto-discover all 12 tools instantly.

Yes, your agent can call `email_verifier` to check the validity of any email address. You can set up a specialized agent to loop through lists returned by `list_leads` and clean them before execution.

Set `cacheToolsList=True` in your configuration to cache the tool definitions. This prevents the SDK from querying the MCP Server on every single turn, reducing latency during high-volume prospecting runs.

The `email_finder` tool returns a clean null or empty response when no match exists. Your agent detects this and can automatically switch to `domain_search` to find alternative contacts at the same company.

This MCP Server runs in a zero-trust, ephemeral V8 isolate sandbox. Your lead data, including prospect emails and domain names, is never stored or logged on our servers; it passes directly to the API endpoint.

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