How to Use the Apollo.io MCP in OpenAI Agents SDK

Q: How do I configure the Apollo.io tools inside my OpenAI Agents SDK pipeline?

You initialize the connection using MCPServerStreamableHttp pointing to your Vinkius endpoint. Pass this server object into your Agent constructor's mcpservers list to auto-discover all twelve tools instantly.

Q: Can the OpenAI Agents SDK handle Apollo.io rate limits automatically?

Yes, by combining the SDK's built-in retry policies with getcreditinfo to monitor your remaining allowance. Your agent can check its status before running bulk enrichment tasks to avoid API exhaustion.

Build production-grade outbound pipelines using the OpenAI Agents SDK to safely search, enrich, and sequence Apollo.io contacts.

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Connect Apollo.io MCP to OpenAI Agents SDK

Create your Vinkius account to connect Apollo.io 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 Apollo.io with OpenAI Agents SDK

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Guarded prospecting with OpenAI Agents SDK

`search_people` is the entry point for your autonomous outbound pipeline, feeding verified contact records directly to your agent. The OpenAI Agents SDK runs this tool inside a secure runtime, checking every returned contact profile against your pre-defined safety guardrails before any action occurs. You prevent bad data from polluting your system by setting strict validation thresholds on the returned payloads. If the search returns stale profiles, the agent halts execution or routes the data to a human reviewer, protecting your domain reputation from day one.

Multi-agent enrichment handoffs

`enrich_company_data` and `enrich_person_data` run sequentially as separate, specialized agents hand off tasks within the OpenAI ecosystem. The first agent identifies the target account, while the second agent pulls down deep metadata to build a complete profile. This separation of concerns means your primary prospecting agent doesn't waste context window tokens on raw data processing. The OpenAI tracing dashboard logs every transition, letting you debug exactly how your agents build these corporate profiles in real time.

Automating sequences via MCP Server

`add_to_sequence` enrolls high-value prospects into your active outreach campaigns without manual intervention. Your agent checks the queue using `list_sales_sequences` to pick the right sequence based on the prospect's title and company size. By connecting this MCP Server directly to your OpenAI agent, you remove the latency of middleware platforms. The agent reads your available sender accounts with `list_connected_emails` and starts the sequence immediately after validating the contact details.

Setup guide

Set up Apollo.io 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 Apollo.io tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Apollo.io 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="Apollo.io Agent",
            instructions="You have access to Apollo.io 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 Apollo.io. 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 Apollo.io MCP in OpenAI Agents SDK

You initialize the connection using `MCPServerStreamableHttp` pointing to your Vinkius endpoint. Pass this server object into your Agent constructor's `mcp_servers` list to auto-discover all twelve tools instantly.

Yes, by combining the SDK's built-in retry policies with `get_credit_info` to monitor your remaining allowance. Your agent can check its status before running bulk enrichment tasks to avoid API exhaustion.

The SDK uses runtime guardrails that inspect the payload of `enrich_person_data` before passing it to subsequent steps. This prevents your agent from processing empty email fields or invalid phone numbers.

You can restrict tool access by defining explicit tools in your agent's configuration rather than passing the entire server list. This ensures a specialized agent only uses `search_companies` and cannot trigger sequences.

Vinkius runs the server in an ephemeral sandbox, meaning no contact profiles, email addresses, or phone numbers are stored on our servers. All payload data passes directly to your secure OpenAI runtime via HTTPS.

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