mcpField
P
Podwise

Podwise

Remote
podwise.aiMemory & Knowledge0Updated 6d ago

About Podwise

Podwise gives AI agents access to podcast search, transcripts, and content workflows for research, recaps, and note-taking. It combines a remote MCP server with an agent skill for questions, translations, and exports across individual episodes or multiple podcasts.

Key features

  1. 01Search podcasts and episodes
  2. 02Retrieve transcripts, summaries, and chapters
  3. 03Ask questions across transcripts
  4. 04Translate episodes and create clips
  5. 05Export Markdown or SRT

Use cases

  1. 01Catch up on recent episodes from followed shows
  2. 02Research a topic across multiple episodes
  3. 03Create language-learning cards from transcripts
  4. 04Export episode notes and key clips

MCP support

Podwise provides a remote MCP server at https://mcp.podwise.ai/mcp using OAuth 2.0. It exposes tools for podcast search, transcripts, Q&A, translation, and export.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp.podwise.ai/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Podwise Plugin

Claude Code Cursor Codex License: MIT AllMCPs

Turn podcast episodes into AI-powered insights from inside Claude Code, Cursor, Codex and ChatGPT. This plugin bundles the Podwise Agent Skill with the remote Podwise MCP server (https://mcp.podwise.ai/mcp), so installing the plugin wires everything up.

In short: a podcast MCP server for AI agents. Point any MCP client at https://mcp.podwise.ai/mcp and it can search podcasts and episodes, pull a full transcript, read the AI summary, chapters, highlights, Q&A and mind map, ask questions across transcripts, translate an episode, clip key moments, and export notes as Markdown or SRT. The skill teaches your agent how to combine those tools into repeatable workflows.

What's included

ComponentDescription
Skillpodwise — routes your intent to the right podcast workflow
MCP serverRemote HTTP server at https://mcp.podwise.ai/mcp (OAuth)
Workflows

The skill routes your intent automatically:

WorkflowWhat it does
catch-upCatch up on missed episodes from shows you follow
weekly-recapGenerate a weekly listening recap with highlights
episode-notesExport episode summaries and highlights to your PKM
topic-researchResearch a topic across multiple episodes
episode-debateChallenge and stress-test ideas from an episode
language-learningGenerate language flashcards from a transcript
discoverGet personalised podcast recommendations

MCP server and tools

Endpoint: https://mcp.podwise.ai/mcp — Streamable HTTP, OAuth 2.0. No API key lives in this repository. Listed on the official MCP Registry as io.github.hardhackerlabs/podwise (see server.json).

38 tools, grouped:

GroupTools
Accountget_me
Search and discoverysearch_episodes, search_podcasts, get_popular_episodes
Library and historylist_followed_episodes, list_followed_podcasts, list_podcast_episodes, list_my_episodes, set_podcast_follow, set_episode_read
Processing and importprocess_episode, import_episode, start_audio_upload, complete_audio_upload
Artifacts and Q&Aget_episode, get_episode_summary, get_episode_transcript, ask_podwise, get_ask_history, translate_episode, list_episode_translations
Clipscreate_clip, get_clip, list_clips, delete_clip, export_clips_markdown, send_clips
Exportexport_episode_markdown, export_episode_srt, send_episode
Enterpriseenterprise_process_audio, enterprise_get_status, enterprise_get_result, enterprise_query_results, enterprise_translate, enterprise_get_translation, enterprise_export, enterprise_get_usage

Full parameter reference: skills/podwise/references/mcp.md.

Install

Claude Code
/plugin marketplace add hardhackerlabs/podwise-plugin
/plugin install podwise@podwise

Then authenticate the MCP server when prompted (OAuth runs in your browser via /mcp).

Cursor

Open Customize → Plugins → Add → From GitHub Repository and import this repository as a marketplace (use the full URL):

https://github.com/hardhackerlabs/podwise-plugin

Then click Add on podwise and authenticate the MCP server when prompted (Customize → Plugins → podwise → Authenticate).

Once Podwise is listed in the Cursor Marketplace, you can also install it from any agent chat:

/add-plugin podwise

The MCP server alone is also available as a one-click install from cursor.directory.

Codex / ChatGPT
codex plugin marketplace add hardhackerlabs/podwise-plugin
codex plugin add podwise@podwise

Then complete the OAuth flow when prompted.

Other agents (skills only)

If your agent reads skills directly but does not install plugins, install the skill and add the MCP server manually:

npx skills add hardhackerlabs/podwise-plugin

Then add the server to your MCP configuration. Use the transport name your client expects — http for Claude Code-style clients (as in .mcp.json), streamable-http for Agent Plugins clients (as in mcp.json):

{ "mcpServers": { "podwise": { "type": "http", "url": "https://mcp.podwise.ai/mcp" } } }

Usage

Once the plugin is installed and authenticated, just ask. For example:

  • "Catch me up on this week's podcast episodes"
  • "Summarize this podcast episode: "
  • "Research what podcasts say about "
  • "Write my weekly listening recap"
  • "Make language-learning cards from this episode's transcript"

The skill checks the connection with get_me first, then routes the request to the matching workflow.

Requirements

  • A Podwise account. The MCP server uses OAuth 2.0; no API key is stored in this repository.
  • Network access to https://mcp.podwise.ai/mcp.
  • Some capabilities require a Podwise Pro or Enterprise plan; the enterprise_* tools are for Enterprise-plan API usage. See podwise.ai for plans.

Remote / SSH note: the host's HTTP MCP OAuth uses a loopback callback, which does not work when the host runs on a machine different from your browser. Use a connection method supported by your host, or see the troubleshooting docs at https://docs.podwise.ai. Do not run third-party proxy commands to work around authentication.

Repository layout

podwise-plugin/                            # this repository is the plugin (source: "./")
├── .claude-plugin/
│   ├── marketplace.json                   # Claude Code marketplace
│   └── plugin.json                        # Claude Code plugin manifest
├── .codex-plugin/plugin.json              # Codex / ChatGPT client manifest
├── .cursor-plugin/
│   ├── marketplace.json                   # Cursor marketplace
│   └── plugin.json                        # Cursor plugin manifest
├── .agents/plugins/marketplace.json       # Codex marketplace
├── plugin.json                            # Portable Agent Plugins manifest
├── mcp.json                               # Remote MCP server config (Agent Plugins, streamable-http)
├── .mcp.json                              # Remote MCP server config (Claude Code and Codex, http)
├── server.json                            # MCP registry manifest (official registry, aggregators)
├── skills/podwise/                        # The Podwise skill
│   ├── SKILL.md
│   ├── references/
│   ├── workflows/
│   └── agents/openai.yaml
└── assets/

The MCP definition is duplicated as mcp.json (portable Agent Plugins, streamable-http) and .mcp.json (referenced by the Claude Code and Codex manifests, http). Keep the transport type matching each platform.

Brand assets

AssetFileSizeDeclared in
Logoassets/logo.png1024×1024 PNG.cursor-plugin/plugin.json (logo), .codex-plugin/plugin.json and plugin.json (interface.logo)
Composer iconassets/composer-icon.png256×256 PNG.codex-plugin/plugin.json and plugin.json (interface.composerIcon), shown in the chat composer

Brand color is #7948E8.

Privacy and support

License

MIT © Podwise

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.