# OPML Podcast & RSS Parser MCP for AI Agents AI Agent Connect

> OPML Podcast & RSS Parser turns your exported subscription files into clean JSON data. It lets your AI client read your actual listening history from apps like Apple Podcasts or Feelly so it can give you better recommendations and analyze your interests without getting bogged down by messy XML code.

## Overview
- **Category:** productivity
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_YR46PjFoCF3LaMb9sA2tHNa3Kujg7ua5Eta5uJGY/ai-agent-connect
- **Tags:** rss, podcast-management, xml-parsing, data-transformation, content-curation, subscription-management

## Description

OPML Podcast & RSS Parser fixes the problem of trying to feed messy XML files into your AI client. If you want your agent to recommend new shows based on what you actually listen to, you usually have to export an .opml file from apps like Apple Podcasts, Pocket Casts, or Feedly. These files are full of nested tags and junk that make it hard for an agent to see the actual content. This Connector takes that file and flattens it into a simple, structured list of your subscriptions, stripping out all the unnecessary noise. It's a great way to give your agent a clear map of your media habits while keeping things local. Since the parsing happens on your machine, your subscription data stays private. You can find this in the Vinkius catalog to help your agent become a personal content curator that actually understands your taste.

## Tools

### parse_opml_feeds
Converts an OPML file into a clean JSON list of subscriptions. It handles the heavy lifting of stripping out useless XML tags.

## Prompt Examples

**Prompt:** 
```
Read my podcasts.opml file and recommend 3 new tech podcasts I might like.
```

**Response:** 
```
Based on your 15 current tech subscriptions (like Lex Fridman), I highly recommend:

1. **Hard Fork**
2. **Syntax**
3. **The Vergecast**
```

**Prompt:** 
```
Extract all the RSS URLs from my Feedly export and format them as a Markdown table.
```

**Response:** 
```
| Title | RSS Feed URL |
|-------|-------------|
| Wired | wired.com/feed |
| TechRadar | techradar.com/rss |
```

**Prompt:** 
```
Analyze my OPML file and tell me what my primary interests are.
```

**Response:** 
```
Looking at your 45 subscriptions, your primary interests are:

* **Artificial Intelligence** (12 feeds)
* **Economics** (8 feeds)
* **Design** (5 feeds)
```

## Capabilities

### Convert OPML to JSON
Turn messy XML exports into a clean, structured list of your subscriptions.

### Feed your AI history
Give your agent a clear view of every podcast and RSS feed you currently subscribe to.

### Extract subscription URLs
Pull out all the direct links from your Feedly or podcast app exports instantly.

### Analyze listening interests
Let your agent identify the core themes in your media consumption by looking at your feeds.

### Generate custom recommendations
Get personalized suggestions based on your actual subscription data rather than generic trends.

## Use Cases

### Personalized Show Recommendations
A user asks for 3 new tech shows. The agent uses parse_opml_feeds to see they follow specific niche shows and then suggests similar high-quality content.

### Content Interest Audit
A user wants to know what they spend the most time on. The agent parses the OPML and categorizes the feeds into Finance, Tech, and Hobbies.

### Feed Migration List
A user moves from one RSS reader to another and wants a clean list of all URLs from their old export to set up the new one.

### Interest Mapping
A user asks what they actually read about. The agent summarizes 50+ feeds into five core topics based on the parsed data.

## Benefits

- Stop wasting tokens on messy XML. By using parse_opml_feeds, your agent only sees the relevant data, keeping your context window clean.
- Get hyper-personalized content. Instead of generic tech recs, your agent can see you listen to specific niche shows and suggest similar ones.
- Maintain your privacy. The parsing happens on your machine, so your private subscription list isn't sent to a third-party server.
- Handle multiple platforms. It works with Apple Podcasts, Pocket Casts, Feedly, and any other standard OPML exporter you use.
- Quick data extraction. Use the parser to instantly turn a massive export into a Markdown table or a summary of your interests.

## How It Works

The bottom line is your agent gets a clear, noise-free map of your content subscriptions.

1. Export your .opml file from your podcast app or RSS reader.
2. Provide the local file path to the parse_opml_feeds tool.
3. Receive a clean JSON list of your subscriptions for your agent to analyze.

## Frequently Asked Questions

**How does the OPML Podcast & RSS Parser help me find new shows?**
It reads your current subscriptions to understand your specific tastes, then suggests new content that actually fits your style instead of just giving you generic popular hits.

**Can I use the OPML Podcast & RSS Parser with Feedly?**
Yes, it works with any standard OPML export, including those from Feedly, Pocket Casts, and Apple Podcasts.

**Is my subscription data safe with the OPML Podcast & RSS Parser?**
Yes, the parsing happens locally on your machine. Your data isn't uploaded to a third-party server, keeping your habits private.

**What is an OPML file?**
It's a standard format used by podcast apps and RSS readers to store your subscription list. This Connector turns that file into a format your AI can read easily.

**Will the OPML Podcast & RSS Parser save me tokens?**
Yes, because it flattens the XML into a clean JSON list, it removes all the unnecessary tags that usually waste your AI's context window.

**How do I get my OPML file?**
You can usually find an Export option in the settings of your podcast app or RSS reader. Once you have the file, you just give the path to your agent.

**Does it support nested subscription categories?**
Yes! It recursively scans through folder nodes (like 'Tech News' -> 'AI') in the OPML file to extract the actual feed URLs, flattening them into a clean list for the AI.

**What specific data is extracted?**
It extracts the Title, the XML (RSS) URL, and the HTML (Website) URL for every single subscription found in the file.

**Can it subscribe to new podcasts for me?**
No, this is a read-only parsing tool. It allows the AI to understand what you currently listen to so it can make intelligent recommendations.