How to Use the Mailshake MCP in OpenAI Agents SDK

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

Pass the endpoint URL into MCPServerStreamableHttp using the required parameters. Wrap it in an async context manager, then hand it to your Agent constructor via the mcpservers list. Set cacheToolsList=True to speed up initialization.

Q: Can the OpenAI Agents SDK pause Mailshake campaigns automatically?

Yes. The framework exposes the pauseoutreachcampaign tool directly to your agent. You can configure guardrails to require human approval before the pause executes.

Build production-ready cold outreach agents with the Mailshake MCP Server and the OpenAI Agents SDK.

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Connect Mailshake MCP to OpenAI Agents SDK

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

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Run Outreach Pipelines with OpenAI Agents SDK

The `list_outreach_campaigns` and `get_campaign_details` tools give your OpenAI agent direct read access to your active cold email pipelines. Your Python code can pull current campaign states and feed them into the agent's context window. If an agent detects a high bounce rate or an error state, it triggers `pause_outreach_campaign` immediately. The SDK's built-in guardrails validate this pause action before execution, preventing accidental shutdowns of healthy campaigns.

Inject Prospects and Track Lead History

The `add_prospects_to_campaign` tool accepts a JSON payload to push new contacts straight into active sequences. Your agent handles the data mapping from your internal database and fires the tool. Once prospects are in the system, agents check their status using `list_campaign_leads` and `get_lead_history`. You get full tracing in the OpenAI dashboard for every lead lookup the agent performs.

Read and Audit Sent Emails

The `list_outreach_messages` tool pulls the raw logs of sent and received emails across your sequences. You configure your agent to run this check on a schedule. When an agent needs the exact text sent to a prospect, it calls `get_message_content`. Specialized agents can then hand off this text to a writing agent to draft personalized follow-ups.

Setup guide

Set up Mailshake 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 Mailshake tools at runtime.
3

Create your Agent

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

Run the agent

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

Pass the endpoint URL into `MCPServerStreamableHttp` using the required parameters. Wrap it in an async context manager, then hand it to your Agent constructor via the `mcp_servers` list. Set `cacheToolsList=True` to speed up initialization.

Yes. The framework exposes the `pause_outreach_campaign` tool directly to your agent. You can configure guardrails to require human approval before the pause executes.

It happens automatically. Once you attach the MCP Server to the agent, it reads the schema for all nine tools. You do not need to manually define the JSON inputs for prospect creation.

The API rejects the malformed JSON payload. The SDK catches this error and logs it in your OpenAI dashboard trace, allowing the agent to attempt a retry or escalate the failure.

The server accesses raw email copy, prospect email addresses, and campaign performance metrics. You control access by issuing a single endpoint token, and the V8 Isolate Sandbox destroys the connection state immediately after the agent finishes its run.

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