How to Use the Miniflux (RSS Reader) MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK filter my feeds automatically?

Yes. Your agent uses listentries to inspect new content and updateentriesstatus to mark items as read based on your custom criteria.

Control your RSS feeds directly within OpenAI Agents SDK. Manage subscriptions and triage articles without leaving your agent pipeline.

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Connect Miniflux (RSS Reader) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Miniflux (RSS Reader) 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 Miniflux (RSS Reader) with OpenAI Agents SDK

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Full RSS lifecycle management

Your agent handles feed maintenance by calling `create_feed` or `delete_feed` to keep your reading list current. It automates the setup process so you don't have to manually manage URLs. You'll find that `refresh_all_feeds` ensures your data is always current. This MCP Server lets your agent monitor updates across your entire subscription base.

Intelligent entry triage

Use `list_entries` to pull content into your agent's context window for analysis. Your agent can then decide which articles warrant attention based on its own internal logic. Once the agent finishes reviewing, it uses `update_entries_status` to clear your inbox. This keeps your feed reader clean and focused on unread items.

Deep content extraction

The `fetch_entry_content` tool retrieves the full body of an article when the feed only provides a summary. Your agent then processes the text to summarize or categorize findings. After extraction, the agent applies labels using `create_category` to organize your library. It creates a structured, searchable archive that reflects your specific interests.

Setup guide

Set up Miniflux (RSS Reader) 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 Miniflux (RSS Reader) tools at runtime.
3

Create your Agent

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

Run the agent

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

The server connects via HTTP transport. You initialize the connection in your Python script and pass the toolset directly to the agent constructor for immediate use.

Yes. Your agent uses `list_entries` to inspect new content and `update_entries_status` to mark items as read based on your custom criteria.

It relies on your API key for authentication. You control the scope of the agent's access by providing a key with the necessary permissions for your account.

It processes feeds as fast as the Miniflux API allows. You can use `refresh_category` to target specific groups if you have a large number of subscriptions.

The MCP Server only touches your feed metadata and article text. No personal credentials or database configurations are exposed outside your local agent environment.

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