How to Use the Medium Alternative MCP in OpenAI Agents SDK

Push content to your profile using the Medium Alternative MCP Server directly from your OpenAI Agents SDK production pipeline.

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Connect Medium Alternative MCP to OpenAI Agents SDK

Create your Vinkius account to connect Medium Alternative 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 Medium Alternative with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Automated story publishing for OpenAI Agents SDK

Stop manual drafting and let your agent handle the heavy lifting. The `create_post` and `create_publication_post` tools allow your code to push stories straight to your feed without leaving the terminal. Your agent checks the content, formats it, and fires the request. It's a clean way to handle your writing queue while the agent maintains state across your deployment.

Profile and publication auditing

Run `get_me` to pull your current authenticated profile data into your agent's context. It gives the agent a clear view of who is talking to the API. Use `list_publications` to see where you have posting access. You'll know exactly which publication to target before the agent attempts a write operation.

Manage your editorial team

The `list_contributors` tool lets your agent fetch a list of everyone authorized to write for your publications. It's useful for verifying access before triggering automated workflows. This MCP Server provides the raw data your agent needs to audit permissions. You keep full control over who contributes to your content strategy.

Setup guide

Set up Medium Alternative 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 Medium Alternative tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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Common questions about Medium Alternative MCP in OpenAI Agents SDK

You handle authentication by providing your integration token through the environment variables managed by your agent. The server uses this token for every request, keeping your credentials separate from the agent logic.

Yes, but you should implement client-side backoff logic in your agent code to respect API rate limits. The server acts as a direct pipe, so your agent is responsible for pacing the requests.

The current toolset focuses on publishing stories immediately. You can use the provided tools to push finished content, but you need to handle draft states within your own application logic.

The agent will catch the exception and report the error code returned by the API. You can then use your agent's tracing features to inspect the payload and debug the failure.

The server only touches the specific profile and publication data necessary to perform your requested actions. Your data stays in transit between your agent and the API, never stored on the server side.

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