# mcp-podcast-parser

> mcp-podcast-parser — pipeworx-io-mcp-podcast-parser. Use this tool when you need to analyze and identify repeated content across multiple podcasts. The mcp-podcast-parser solves the problem of tracking recurring themes, topics, or phrases in a large number of podcasts, providing insights into common trends and patterns. It takes podcast data as input and outputs analyzed results, ideal for use cases such as content research, trend analysis, or media monitoring.

Canonical page: https://skillsregistry.net/skills/pipeworx-io-mcp-podcast-parser  
JSON: https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-podcast-parser

## Description

podcast-parser (CanonCannon) — what gets repeated across 162 tracked podcasts.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/pipeworx-io/mcp-podcast-parser)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "pipeworx-io-mcp-podcast-parser"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-podcast-parser` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-podcast-parser/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt