RSS Feed Parser MCP Server for LlamaIndexGive LlamaIndex instant access to 1 tools to Parse Rss Feed

Name: RSS Feed Parser
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add RSS Feed Parser as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The RSS Feed Parser MCP Server for LlamaIndex is a standout in the Productivity category — giving your AI agent 1 tools to work with, ready to go from day one.

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python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to RSS Feed Parser. "
            "You have 1 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in RSS Feed Parser?"
    )
    print(response)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About RSS Feed Parser MCP Server

Your content marketing agent needs to monitor 20 competitor blogs, 5 industry news feeds, and 3 podcast channels. Without a parser, it scrapes HTML — inconsistent, slow, and full of noise.

LlamaIndex agents combine RSS Feed Parser tool responses with indexed documents for comprehensive, grounded answers. Connect 1 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

RSS and Atom feeds are the web's native content API. This MCP parses them into clean JSON objects with titles, links, publication dates, authors, categories, and full content — ready for summarization, curation, or automated distribution.

The Superpowers

RSS 2.0 + Atom: Both formats parsed identically into a unified JSON structure.
Full Content: Extracts title, link, date, author, categories, enclosures (podcasts), and content/summary.
No Scraping: Clean, structured data from the feed XML — no HTML parsing, no DOM traversal.
Podcast Ready: Enclosure extraction for audio/video URLs, durations, and file sizes.

The RSS Feed Parser MCP Server exposes 1 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 1 RSS Feed Parser tools available for LlamaIndex

When LlamaIndex connects to RSS Feed Parser through Vinkius, your AI agent gets direct access to every tool listed below — spanning rss, atom, content-aggregation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

parse

Parse rss feed on RSS Feed Parser

Pass the raw XML string and receive a structured JSON with feed metadata and up to 20 items. This is essential for content marketing agents monitoring blogs, news aggregators, and podcast feeds. Never try to parse XML manually — use this engine for deterministic extraction. Parses RSS 2.0 and Atom feed XML into structured JSON objects. Extracts title, description, items with links, dates, categories, and content snippets

Connect RSS Feed Parser to LlamaIndex via MCP

Follow these steps to wire RSS Feed Parser into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 1 tools from RSS Feed Parser

Why Use LlamaIndex with the RSS Feed Parser MCP Server

LlamaIndex provides unique advantages when paired with RSS Feed Parser through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine RSS Feed Parser tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain RSS Feed Parser tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query RSS Feed Parser, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what RSS Feed Parser tools were called, what data was returned, and how it influenced the final answer

RSS Feed Parser + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the RSS Feed Parser MCP Server delivers measurable value.

Hybrid search: combine RSS Feed Parser real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query RSS Feed Parser to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying RSS Feed Parser for fresh data

Analytical workflows: chain RSS Feed Parser queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for RSS Feed Parser in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with RSS Feed Parser immediately.

"Monitor TechCrunch's RSS feed and give me the latest 5 articles with titles and publish dates."

"Parse our company blog feed and extract all articles tagged 'product-update' from the last 30 days."

"Get the latest episode URLs from this podcast RSS feed for our newsletter."

Troubleshooting RSS Feed Parser MCP Server with LlamaIndex

Common issues when connecting RSS Feed Parser to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

RSS Feed Parser + LlamaIndex FAQ

Common questions about integrating RSS Feed Parser MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query RSS Feed Parser tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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