How to Use the Buy Me A Coffee MCP in OpenAI Agents SDK

Track your Buy Me A Coffee earnings and supporter data directly inside your OpenAI Agents SDK production pipeline.

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Connect Buy Me A Coffee MCP to OpenAI Agents SDK

Create your Vinkius account to connect Buy Me A Coffee 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 Buy Me A Coffee with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Monitor supporter growth with OpenAI Agents SDK

Use `list_supporters` to pull your latest backers straight into your agent logic. It gives you the raw data needed to trigger custom thank-you workflows or analyze donation trends without leaving your Python code. Your agent handles the heavy lifting by filtering through one-time payments and recurring members. It puts the real-time status of your Buy Me A Coffee community into your codebase.

Validate creator stats in your agent system

Call `get_account_stats` to feed your agent precise financial metrics. It grabs your current earnings and goal progress, allowing your agent to report back on how your project is funding itself. This MCP Server provides the numbers your agent needs to make informed decisions about your creator business. You get direct access to the stats that matter most.

Manage digital goods via OpenAI Agents SDK

Expose your digital products and posts using `list_extras` and `list_posts`. Your agent can now suggest specific downloads or content to users based on what you have already published. This lets your agent act as a curator for your shop. It knows exactly what is available for sale or for your members to view.

Setup guide

Set up Buy Me A Coffee 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 Buy Me A Coffee tools at runtime.
3

Create your Agent

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

Run the agent

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

Use the MCPServerStreamableHttp class to point your agent at the Vinkius endpoint. It maps the tools to your agent automatically, so you can start querying your creator data in your next async loop.

Yes, it manages the flow of data from your account into your agent's memory. You just define the agent, pass the server, and let the tools do the work.

Your data stays private because this MCP server acts as a strict bridge. It only exposes specific account records like supporter lists and post history directly to your local agent instance.

Not really. You just set up the HTTP connection and the tools become available for your agent to call. It keeps your setup clean and focused on your logic.

It uses standard protocol calls to fetch your profile information. Your agent requests the data, the server responds, and you get the info in your console.

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