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PodLearn

Searches podcasts and YouTube, transcribes episodes, searches transcripts, and creates AI lessons through MCP.

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Install PodLearn

Pick your client, then add it in one click or paste the config.

No confirmed install command yet

We only publish a config when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for PodLearn, and we’d rather show nothing than a guess you’d paste into your client.

Open setup steps on GitHub

Overview

PodLearn MCP server connects MCP clients to PodLearn’s podcast and video knowledge service. It can search podcasts, YouTube, episodes, and feeds; transcribe URLs or full feeds; search saved transcripts; and generate lessons or LinkedIn posts. The hosted Streamable HTTP endpoint uses OAuth, with personal tokens available for headless clients. Reach for it when an agent needs to turn long-form audio or video into searchable text, cited excerpts, or structured learning notes.

Use cases

  • Search podcasts about a research topic
  • Transcribe a YouTube lecture
  • Ingest an entire podcast feed
  • Find quotes inside saved transcripts
  • Generate a lesson from an episode

Key features

  • Search podcasts and YouTube
  • Search episodes and podcast feeds
  • Transcribe URLs or complete feeds
  • Search and retrieve saved transcripts
  • Generate structured AI lessons
  • Create LinkedIn posts from lessons

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

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Adoption & maintenance

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Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How PodLearn works

What PodLearn MCP server does

PodLearn MCP server brings podcast and YouTube research into MCP-compatible clients. It searches more than four million podcasts and YouTube content, finds episodes and feed entries, and processes media into transcripts. Once content is in the PodLearn library, an agent can search the transcript text and retrieve the full transcription.

It can generate key takeaways and notes from a transcript, and it includes a tool for converting a lesson into a LinkedIn post. These capabilities make it relevant to the 🎙️ Podcasts category, as well as workflows involving lectures, interviews, conference talks, and other long-form videos.

How it works

PodLearn MCP server is available as a hosted Streamable HTTP service at https://podlearn.ai/mcp. An MCP client connects to that endpoint and authenticates with OAuth through a PodLearn account. Headless clients can use a personal API token in an Authorization: Bearer ... header instead. Tokens should not be placed in the URL.

The tool set covers discovery, ingestion, retrieval, and transformation. Search tools locate podcasts, YouTube videos, or episodes. list_feed_episodes enumerates episodes from a feed. transcribe_url handles one podcast or YouTube URL, while transcribe_feed can process a complete feed in bulk. get_transcription retrieves stored text, and search_transcription finds terms or passages within saved transcripts.

Setup and configuration

Claude Code users can install the repository’s plugin through the Claude Code marketplace. The plugin includes both a routing skill and the MCP server, so a separate manual MCP registration is not required for that installation path. After restarting Claude Code, authenticate the podlearn server from /mcp and approve read-only or read-and-write access in the browser.

For direct connections, configure an MCP client with the hosted URL and OAuth. The README gives direct commands for Claude Code and Codex, and also documents custom-connector setup for Claude. Cursor and other MCP clients can use the same Streamable HTTP endpoint when they support the required connection and authentication flow.

Limitations and notes

A PodLearn account is required. Reading and searching transcripts already stored in the library is free, while transcribe_url, transcribe_feed, and generate_lesson consume PodLearn credits. The service starts with two free credits, and the skill confirms paid actions before charging.

Permissions affect available operations. A read-only OAuth approval will not provide write access; re-authentication is required when the client reports an insufficient scope. For browserless use, create a personal token in PodLearn settings and send it as a bearer header. The repository is licensed under AGPL-3.0.

Read the full README View source on GitHub

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Frequently Asked Questions about PodLearn

PodLearn is an MCP server that connects Claude and other MCP clients to the PodLearn podcast and video knowledge service. Its main tools search podcasts and YouTube, transcribe URLs or feeds, search saved transcripts, retrieve transcriptions, generate lessons, and create LinkedIn posts.

Install the bundled plugin through the Claude Code marketplace, or connect an MCP client directly to `https://podlearn.ai/mcp`. Claude Code and Codex have documented command-line setup, while direct connections use Streamable HTTP with OAuth.

Yes, PodLearn works with Cursor when configured as an MCP connection. Point Cursor at the Streamable HTTP endpoint and authenticate with OAuth, or use a personal API token as a bearer header for a headless setup.

Use the `transcribe_feed` tool to process a podcast feed in bulk. You can first use `list_feed_episodes` to inspect the feed, and the resulting transcripts can then be retrieved or searched with the transcription tools.

Transcribing a URL, transcribing a feed, and generating a lesson use PodLearn credits. Reading and searching transcripts already in the library do not, and the Claude Code skill confirms the cost before a paid action.

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