PodCrawlerMCP

PodCrawlerMCP

By infinitimeless GitHub

MCP server for podcast discovery through web crawling

podcrawler podcast-discovery
Overview

what is PodCrawlerMCP?

PodCrawlerMCP is an MCP (Model Context Protocol) server designed for podcast discovery through web crawling, enabling AI assistants to find podcast episodes on specific topics by crawling the web for RSS feeds.

how to use PodCrawlerMCP?

To use PodCrawlerMCP, install it via pip or Poetry, run the server, and integrate it with AI assistants like Claude by configuring the MCP server settings.

key features of PodCrawlerMCP?

  • 🕸️ Crawls podcast directories to discover RSS feeds
  • 🎙️ Parses RSS feeds to extract episode data
  • 🔍 Filters episodes by topic or domain
  • 🔌 Exposes functionality through MCP tools
  • 🤖 Seamlessly integrates with AI assistants like Claude

use cases of PodCrawlerMCP?

  1. Discovering podcasts on specific topics such as technology or history.
  2. Enabling AI assistants to provide users with relevant podcast recommendations.
  3. Automating the process of finding and filtering podcast episodes based on user interests.

FAQ from PodCrawlerMCP?

  • Can PodCrawlerMCP discover podcasts on any topic?

Yes! PodCrawlerMCP can discover podcasts on a wide range of topics by filtering RSS feeds.

  • Is PodCrawlerMCP easy to integrate with AI assistants?

Yes! PodCrawlerMCP is designed for seamless integration with AI assistants like Claude.

  • What programming language is PodCrawlerMCP written in?

PodCrawlerMCP is written in Python.

Content

PodCrawlerMCP

License: MIT

An MCP (Model Context Protocol) server for podcast discovery through web crawling. PodCrawlerMCP enables AI assistants to find podcast episodes on specific topics by crawling the web for RSS feeds.

Features

  • 🕸️ Crawls podcast directories to discover RSS feeds
  • 🎙️ Parses RSS feeds to extract episode data
  • 🔍 Filters episodes by topic or domain
  • 🔌 Exposes functionality through MCP tools
  • 🤖 Seamlessly integrates with AI assistants like Claude

Installation

pip install podcrawler-mcp

Or with Poetry:

poetry add podcrawler-mcp

Quick Start

Run the server directly:

python -m podcrawler.server

Or in your Python code:

from podcrawler import PodCrawlerServer

server = PodCrawlerServer()
server.run()

Integrating with Claude Desktop

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "podcrawler": {
      "command": "python",
      "args": ["-m", "podcrawler.server"]
    }
  }
}

Available Tools

discover_podcasts

Discovers podcasts on a specific topic.

Parameters:

  • topic (string): The topic to search for (e.g., "technology", "history")
  • max_results (integer, optional): Maximum number of results to return (default: 10)

Example Usage:

What are some science podcasts about black holes?

Project Structure

podcrawler-mcp/
├── podcrawler/                # Main package
│   ├── __init__.py            # Package initialization
│   ├── server.py              # MCP server implementation
│   ├── tools/                 # MCP tools
│   │   ├── __init__.py
│   │   └── discovery.py       # Podcast discovery tool
│   ├── crawler/               # Web crawling components
│   │   ├── __init__.py
│   │   ├── spider.py          # Web crawler implementation
│   │   └── parser.py          # RSS feed parser
│   └── utils/                 # Utility functions
│       ├── __init__.py
│       ├── filtering.py       # Topic filtering utilities
│       └── formatting.py      # Output formatting utilities
├── tests/                     # Tests
│   ├── __init__.py
│   └── test_server.py         # Server tests
├── examples/                  # Usage examples
│   └── basic_discovery.py     # Basic discovery example
├── pyproject.toml             # Project configuration
├── README.md                  # Project documentation
├── LICENSE                    # MIT License
└── CONTRIBUTING.md            # Contribution guidelines

Development

  1. Clone the repository

    git clone https://github.com/infinitimeless/podcrawler-mcp.git
    cd podcrawler-mcp
    
  2. Install dependencies using Poetry

    poetry install
    
  3. Run tests

    poetry run pytest
    

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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