How to Use the AeroLeads MCP in OpenAI Agents SDK

Q: How do I connect the AeroLeads MCP Server to the OpenAI Agents SDK?

Install the openai-agents package via pip. Set up the Vinkius endpoint using MCPServerStreamableHttp and pass it to your Agent constructor. The SDK auto-discovers all twelve tools immediately.

Q: Can the OpenAI Agents SDK track my AeroLeads credit usage?

Yes, your agent can call the getcreditbalance tool. You can set up safety constraints to prevent it from exhausting your account limit during large prospecting runs.

Q: What happens if an agent grabs the wrong contact?

You can program a specialized agent to review lists using getleaddetails. If the criteria fail, it triggers deletelead to purge the record.

Q: Does this MCP Server support webhook management?

The listwebhooks tool lets your agent see active payload destinations. It helps sync your sales data with external CRMs.

Build production sales agents with the AeroLeads MCP Server and OpenAI Agents SDK. Find verified contacts and manage lead lists safely.

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Connect AeroLeads MCP to OpenAI Agents SDK

Create your Vinkius account to connect AeroLeads 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 AeroLeads with OpenAI Agents SDK

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Automate prospect discovery with OpenAI Agents SDK

Your agent needs to find decision-makers at specific companies. Give it a domain name, and the `search_domain_leads` tool pulls back a list of potential contacts. It grabs verified emails and phone numbers instantly. You do not have to write custom scrapers or manage proxy rotation. Because you are building with OpenAI's built-in guardrails, your agent validates the action before burning credits. It checks your balance using `get_credit_balance` before hitting the search endpoint. Then it saves the best matches directly to your account with `add_new_lead`.

Deep LinkedIn enrichment via MCP

Sometimes a name and an email are not enough. When your system needs more context for a personalized outreach sequence, the `get_linkedin_details` tool extracts full profile data. It pulls current titles, work history, and company details straight from the source. Every single API call routes through the OpenAI dashboard for full tracing. You see exactly what the agent searched for when it called `find_email_by_name`. If a specialized research agent finds the prospect, it hands the enriched profile off to an outreach agent immediately.

Native lead list operations

Managing captured contacts usually requires jumping between tabs. Now your code handles it natively. The agent calls `list_prospecting_lists` to find the right bucket, then uses `list_captured_leads` to review who is already there. It prevents duplicates automatically. Mistakes happen during automated prospecting. If a bad fit sneaks in, the `delete_lead` tool removes them. Your agent keeps the pipeline clean without human intervention.

Setup guide

Set up AeroLeads 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 AeroLeads tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate AeroLeads 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="AeroLeads Agent",
            instructions="You have access to AeroLeads tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AeroLeads. 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.

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Common questions about AeroLeads MCP in OpenAI Agents SDK

Install the `openai-agents` package via pip. Set up the Vinkius endpoint using `MCPServerStreamableHttp` and pass it to your Agent constructor. The SDK auto-discovers all twelve tools immediately.

Yes, your agent can call the `get_credit_balance` tool. You can set up safety constraints to prevent it from exhausting your account limit during large prospecting runs.

You can program a specialized agent to review lists using `get_lead_details`. If the criteria fail, it triggers `delete_lead` to purge the record.

The `list_webhooks` tool lets your agent see active payload destinations. It helps sync your sales data with external CRMs.

Vinkius runs the server in an ephemeral V8 Isolate Sandbox. When your code fetches names and phone numbers, the data passes straight to your environment. Nothing gets logged or stored on our infrastructure.

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