How to Use the BigMailer MCP in OpenAI Agents SDK

Q: How do I register the BigMailer MCP Server in my OpenAI Agents SDK project?

First, run pip install openai-agents in your environment. Next, configure the MCPServerStreamableHttp client with your Vinkius BigMailer endpoint and pass it to the agent's server list.

Q: Can I cache the BigMailer tool definitions to speed up my OpenAI Agents SDK runs?

Yes, you can set cacheToolsList=True in your OpenAI Agents SDK initialization to cache the BigMailer tool definitions. This stops your agent from making network calls to discover tools like listcontactlists on every single run.

Q: How does the OpenAI Agents SDK handle tool execution errors from BigMailer?

If a BigMailer tool like getcontactlist fails, the OpenAI Agents SDK catches the exception and returns the raw error to your agent. Your agent can then analyze the failure and try to fix the parameter dynamically.

Trigger BigMailer contact updates and campaign audits directly from your OpenAI Agents SDK production pipelines.

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Connect BigMailer MCP to OpenAI Agents SDK

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

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Secure BigMailer updates with OpenAI Agents SDK guardrails

This MCP Server exposes the `add_contact` tool to your OpenAI agents, letting them sync user data without manual BigMailer API calls. Because you are using the OpenAI Agents SDK, you can set up strict runtime validation guardrails that inspect payload schemas before your agent pushes email updates to your BigMailer brand list. The OpenAI Agents SDK intercepts the tool call, ensuring your agent doesn't write corrupted emails or incorrect custom properties to BigMailer. If some agent tries to push a malformed `add_contact` payload, your OpenAI validation rules kill the execution before it ever hits BigMailer.

Let specialized agents run deep campaign audits

Use the `list_bulk_campaigns` and `get_bulk_campaign` tools to build a dedicated BigMailer marketing auditor using the OpenAI Agents SDK. You can configure a supervisor agent that delegates work to a specialist, pulling BigMailer campaign metrics and formatting them for your internal OpenAI pipeline alerts. The OpenAI Agents SDK manages the handoffs between these specialized BigMailer agents. One agent fetches the BigMailer list, another inspects the campaign details, and a third drafts the performance summary based on the raw JSON payload.

Map brand structures across your LLM workflows

The `list_brands` and `list_templates` tools allow your OpenAI agents to inspect your entire BigMailer email marketing setup using the MCP standard. Instead of hardcoding BigMailer template IDs, your OpenAI agent queries your active templates dynamically to select the right asset for transactional sends. By calling `get_brand_properties`, your OpenAI agent figures out which custom BigMailer fields are available for personalization. This guarantees that your dynamic BigMailer email campaigns always match the active schema of your OpenAI agent configuration.

Setup guide

Set up BigMailer 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 BigMailer tools at runtime.
3

Create your Agent

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

Run the agent

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

First, run `pip install openai-agents` in your environment. Next, configure the `MCPServerStreamableHttp` client with your Vinkius BigMailer endpoint and pass it to the agent's server list.

Yes, you can set `cacheToolsList=True` in your OpenAI Agents SDK initialization to cache the BigMailer tool definitions. This stops your agent from making network calls to discover tools like `list_contact_lists` on every single run.

If a BigMailer tool like `get_contact_list` fails, the OpenAI Agents SDK catches the exception and returns the raw error to your agent. Your agent can then analyze the failure and try to fix the parameter dynamically.

You can restrict access by only registering specific BigMailer tools in your OpenAI Agents SDK configuration. This keeps your agent focused and prevents it from executing unauthorized actions.

Your BigMailer email contact records and brand properties are processed in Vinkius's zero-trust V8 sandbox. The OpenAI Agents SDK connects via an encrypted stream, ensuring your subscriber lists are never exposed to public networks.

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