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How to Use the Miniflux (RSS Reader) MCP in LlamaIndex

Index your live news feeds into LlamaIndex using the Miniflux (RSS Reader) MCP Server.

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LlamaIndex

Connect Miniflux (RSS Reader) MCP to LlamaIndex

Create your Vinkius account to connect Miniflux (RSS Reader) to LlamaIndex 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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Semantic search over Miniflux (RSS Reader) data

Pipe `list_entries` output into a vector store to make your entire archive queryable. LlamaIndex treats your feed history as a searchable knowledge base. You can ask questions about past events and get answers grounded in the specific articles you have saved. It turns thousands of entries into a source of truth for your research.

Automated retrieval for LlamaIndex

Configure your index to pull fresh data via `refresh_feed` before running a query. This ensures your RAG pipeline never relies on stale information. The agent fetches the latest entries and updates the index in real-time. You always get the most recent context from your favorite sources.

Manage your reading list from LlamaIndex

Use `toggle_entry_bookmark` to flag articles that you want to keep for long-term reference. The agent marks these items, and your index can prioritize them in future searches. This keeps your most important research materials highlighted. You can later search specifically for bookmarked entries to isolate your high-signal content.

Setup guide

Set up Miniflux (RSS Reader) MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 2

    Connect with BasicMCPClient

    Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.

  3. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Miniflux (RSS Reader) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 4

    Run with any LLM

    Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Miniflux (RSS Reader) tools.",
)
response = await agent.run("List recent Miniflux (RSS Reader) data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Miniflux. 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 Miniflux (RSS Reader) MCP in LlamaIndex

It does. You can convert the tool list from this MCP server into native LlamaIndex tools. This allows your RAG agent to pull live data from your feeds.
You pull the entries into your index, which then creates vector embeddings. Once indexed, you can run semantic queries to find articles across all your feeds.
You can use the filtering arguments in `list_entries` to restrict which feeds your index processes. This keeps your vector store focused on specific topics.
Yes, the tool outputs are structured to work with the standard tool specs. You can map them directly into your agent's execution loop.
Access is restricted to the specific API key you provide. The server acts as a secure bridge, ensuring only authorized queries reach your private feed entries.

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