@SaitoWu: 强烈推荐 WorkBuddy 用户安装这个播客信息源: https://github.com/hardhackerlabs/podwise-cli… 用起来超爽:搜索任意播客、拉取结构化摘要、关键洞见、Mind Map,直接喂给 Work…

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摘要

推荐安装的 podwise-cli 是一款 CLI 工具,可将任意播客内容转化为结构化摘要、关键洞见和思维导图,方便 AI 代理和工作流使用。

✨ 强烈推荐 WorkBuddy 用户安装这个播客信息源: https://t.co/RlhjXHdvMl 用起来超爽:搜索任意播客、拉取结构化摘要、关键洞见、Mind Map,直接喂给 WorkBuddy 写文章、做复盘、生成内容计划……效率直接起飞! https://t.co/29tbjk3I70
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✨ 强烈推荐 WorkBuddy 用户安装这个播客信息源:

https://t.co/RlhjXHdvMl

用起来超爽:搜索任意播客、拉取结构化摘要、关键洞见、Mind Map,直接喂给 WorkBuddy 写文章、做复盘、生成内容计划……效率直接起飞! https://t.co/29tbjk3I70


hardhackerlabs/podwise-cli

Source: https://github.com/hardhackerlabs/podwise-cli

podwise-cli

podwise

CLI client for podwise.ai — turn any podcast episode into AI-powered insights, designed for use in AI agents and skills workflows.

Podwise transforms hours of podcasts into transcripts, summaries, outlines, Q&A, and mind maps. This CLI is purpose-built as a tool for AI agents — letting LLMs, skills runtimes, and automation pipelines fetch structured podcast insights without a browser or human in the loop.

  • 🤖 Looking for ready-to-use agent skills? Jump to Agent Skills
  • 🔌 Looking for mcp server? Jump to MCP Server

Installation

Homebrew (macOS)

brew install hardhackerlabs/podwise-tap/podwise

Automatic Script

Run the following command to install the latest version of podwise:

curl -sL https://raw.githubusercontent.com/hardhackerlabs/podwise-cli/main/install.sh | sh

Manual (Binary)

  1. Download the latest binary for your OS and architecture from GitHub Releases.
  2. Unpack the archive (e.g., tar -xzf podwise_linux_amd64.tar.gz).
  3. Move the podwise binary to a directory in your PATH, for example:
    mv podwise /usr/local/bin/
    
  4. Make sure it’s executable: chmod +x /usr/local/bin/podwise.

From Source

If you have Go installed, you can build and install the binary directly from the source:

git clone https://github.com/hardhackerlabs/podwise-cli.git
cd podwise-cli
go build -o podwise .
# Move the binary to a directory in your PATH, e.g.,
mv podwise /usr/local/bin/

Configuration

Authorize the CLI in your browser and let it save the API key automatically:

# Open the browser authorization flow
podwise auth

# Verify connection
podwise config show

If you already have an API key, you can still set it manually:

podwise config set api_key your-sk-xxxx

The configuration is stored at ~/.config/podwise/config.toml.

Usage

Trending Episodes

podwise popular

Ask AI

# Ask a question answered from podcast transcripts
podwise ask "the future of AI Agents"

Search

# Search episodes by title keywords
podwise search episode "machine learning" --limit 20

# Search podcasts by name
podwise search podcast "Lex Fridman"

Process an Episode

# Podwise episode URL (Recommended)
podwise process https://podwise.ai/dashboard/episodes/7360326

# 小宇宙 episode URL 
podwise process https://www.xiaoyuzhoufm.com/episode/abc123

# Youtube video URL
podwise process https://www.youtube.com/watch?v=d0-Gn_Bxf8s

# local file
podwise process ./episode.mp3

Get Episode Results

# Get summary
podwise get summary https://podwise.ai/dashboard/episodes/7360326

# Get transcript
podwise get transcript <episode-url>

For more details on all available commands and flags, run:

podwise --help

Agent Skills

Prerequisites: Before installing skills, make sure you have completed the Installation and Configuration steps above — the podwise CLI must be installed and your api_key must be set.

Available Workflows

The Podwise skill routes your intent to the right workflow automatically:

WorkflowWhat it does
catch-upCatch up on missed episodes from podcasts you follow
weekly-recapGenerate a weekly listening recap with highlights
episode-notesExport episode summaries and highlights to Notion, Obsidian, or Logseq
topic-researchResearch a topic across multiple podcast episodes
episode-debateChallenge and stress-test ideas from an episode
language-learningGenerate Anki flashcards from a transcript
discoverGet personalised podcast recommendations based on your taste
refine-tasteBuild your listener profile for personalised outputs

How It Works

When you ask the agent something related to podcasts, it:

  1. Loads Podwise CLI reference docs
  2. Matches your intent to the right workflow (if applicable)
  3. Loads and executes the workflow steps, or runs the CLI command directly

Installation

npx skills add hardhackerlabs/podwise-cli

You can also build your own skills on top of the podwise CLI to create custom workflows that fit your needs.

MCP Server

Podwise exposes all its capabilities as an MCP (Model Context Protocol) server, allowing AI assistants (Gemini CLI, Claude Desktop, Cursor, etc.) to search episodes, process media, and retrieve AI-generated content directly as tools.

Start the MCP server (communicates over stdin/stdout):

podwise mcp

The server exposes the following tools:

ToolDescription
search_episodeSearch for podcast episodes by title keywords
search_podcastSearch for podcasts by name
popularList current trending/popular podcast episodes
processSubmit a YouTube / 小宇宙 / Podwise URL or local file for AI processing
get_transcriptFetch the full transcript (text / SRT / VTT)
get_summaryFetch the AI-generated summary and key takeaways
get_qaFetch AI-extracted Q&A pairs
get_chaptersFetch the chapter breakdown with timestamps
get_mindmapFetch the AI-generated mind map
get_highlightsFetch notable highlights with timestamps
get_keywordsFetch topic keywords with descriptions
askAsk the AI a question answered from podcast transcripts
drillList recent episodes for a specific podcast by its Podwise URL
followFollow a podcast by its Podwise URL (idempotent)
unfollowUnfollow a podcast by its Podwise URL (idempotent)
list_episodesList recent episodes from podcasts you follow, filterable by date or day range
list_podcastsList followed podcasts with new episodes, filterable by date or day range
history_readList episodes you have read, sorted by most recent first
history_listenedList episodes you have listened, sorted by most recent first

Installation

  1. Make sure podwise is installed and configured (see Installation and Configuration).

  2. Add the following to your settings file:

{
  "mcpServers": {
    "podwise": {
      "command": "podwise",
      "args": ["mcp"]
    }
  }
}

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