Podcli

by nmbrthirteen

548 downloads

Not rated

GitHub

About

Podcli is an open-source MCP server and CLI that turns long-form podcasts into upload-ready short clips for TikTok, YouTube Shorts, and Reels. It transcribes with Whisper, finds viral moments with Claude or Codex against your show's knowledge base, crops to vertical with face tra

Details

Author: nmbrthirteen
Downloads: 548
Categories: Productivity, Other, Media

- Transcribes with Whisper, providing word-level timestamps and speaker diarization.
- Finds viral moments using AI and a knowledge base, scoring candidates on four dimensions.
- Crops to 1080×1920 with YuNet face detection and speaker-aware tracking.
- Burns in captions in four styles: branded, hormozi, karaoke, subtle.
- Exports with hardware encoding (VideoToolbox, NVENC, VAAPI, CPU fallback).
- Provides 17 MCP tools for transcript, clips, context, and config

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Podcli

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

From the repository

Install by cloning the repository and running ./setup.sh. Requires Node ≥18, Python ≥3.10, and FFmpeg. Use via CLI (./podcli process episode.mp4 --top 8), Web UI (npm run ui), or as an MCP server by adding the provided JSON configuration to Claude Code, Claude Desktop, or Codex. The MCP setup specifies the path to dist/index.js and the Python virtual environment.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "podcli": {
            "podcli": {
                "command": "node",
                "args": [
                    "/path/to/podcli/dist/index.js"
                ],
                "env": {
                    "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
                }
            }
        }
    }
}

McpServers

{
    "podcli": {
        "command": "node",
        "args": [
            "/path/to/podcli/dist/index.js"
        ],
        "env": {
            "PYTHON_PATH": "/path/to/podcli/venv/bin/python3"
        }
    }
}

Open-source AI podcast clipper.
Turn a long episode into short clips with face tracking and burned-in captions. Drive it from the CLI, a web studio, or your coding agent.

That one command transcribes the episode, picks the moments worth clipping, crops to whoever is speaking, and burns the captions in. Transcription and rendering run on your machine. The only network calls are the optional Claude or Codex requests when you use AI clip scoring.

No prerequisites. The installer fetches a self-contained binary, and the first run provisions Python, Node, FFmpeg, whisper.cpp, and the models it needs into a managed folder.

curl -fsSL https://podcli.com/install.sh | sh

irm https://podcli.com/install.ps1 | iex

Runs on macOS (Apple Silicon), Linux (x64 and arm64), and Windows (x64). Intel Mac support is in progress.

podcli # interactive menu, opens the web studio podcli process episode.mp4 # transcribe, pick moments, render clips

Clips land inpodcli-clips/in the directory you ran it from, so each show keeps its own renders. Everything else (knowledge, presets, assets, clip history, cache) lives in one managed folder that follows you between directories. SetPODCLI_OUTPUTto render somewhere fixed instead.

- 9:16, 16:9, or 1:1, with captions sized for each canvas
- Face tracking that follows the speaker, split-screen layouts included
- Multi-segment cuts that drop filler, long pauses, and tangents
- Four caption styles: branded, hormozi, karaoke, subtle
- Logos, intros, outros, and background music from a reusable asset library
- Loudness-normalized audio and hardware encoding on VideoToolbox, NVENC, and VAAPI, with a CPU fallback

- Whisper transcription with speaker diarization, or bring your own transcript as.txt,.srt, or.vtt
- AssemblyAI as an alternative engine, and yt-dlp to pull an episode straight from a URL
- AI scoring against your knowledge base, checked against your episode database so it stops resuggesting moments you already published
- Audio energy and laughter detection to build highlight reels

- Library, episode workspace, per-clip detail, highlights, thumbnails, content, analytics, assets, knowledge, config, integrations, and MCP setup
- ⌘Kcommand palette across pages, clips, and assets
- Titles, descriptions, tags, and hashtags, with any section regenerated on your own guidance
- Thumbnail studio for 16:9 and 9:16, with frame and text options
- Transcript corrections that carry through to every render

- 26 MCP tools, so an agent can transcribe, score, render, and publish through conversation
- YouTube publishing plus performance analytics to see which clips landed
- DaVinci Resolve export as FCPXML when you want to finish by hand
- Presets, clip history with duplicate detection, and a transcript cache

If you are weighing podcli against the cloud clippers, this is the difference:

- Runs locally. Transcription and rendering happen on your machine by default, so episodes stay there. Only the optional cloud engine (AssemblyAI) and publishing to YouTube send anything out.
- Free and open source under AGPL-3.0. Exports are unlimited, full quality, and watermark-free.
- Agent-native. 26 MCP tools let Claude Code or Codex drive the whole flow, transcription through publishing.
- A knowledge base keeps titles, captions, and descriptions in your show's voice, and stops the engine from resuggesting moments you already published.
- DaVinci Resolve handoff. Export any clip as FCPXML when you want to finish the edit yourself.

podcli is anMCPserver, so an agent can transcribe, suggest clips, and render them through conversation.

podcli mcp install # registers it with Claude Code

Claude Desktop and Codex setup is in the MCP docs.

PodStackships with podcli as a set of Claude Code slash commands. They take a transcript to a publish-ready package: scored moments, titles, descriptions, thumbnail briefs, a brand review, and a publish checklist.

The commands live in.claude/commands/.CLAUDE.mddescribes each one.

Docs are open source at nmbrthirteen/podcli-docs.

See CONTRIBUTING.mdfor the dev setup and conventions, and RELEASE.mdfor how releases are cut.

Content workflow powered by PodStack, inspired by gstackby Garry Tan.

Need podcli without AGPL terms? A commercial license is available. Email siradze@nikusha.mewith a one-line description of your use case.

Audio tools MCP server for professional audio editing and AI augmentation

The World's First AI Music MCP Beyond images and video, your agent can now generate music.

MCP server for Audacity 3.x with 131 tools — effects, cleanup, mastering, format conversion, transcription.

Enables AI assistants to interact with DaVinci Resolve Studio for advanced control over video editing, color grading, and audio.

Feed any YouTube video, article, PDF, or image into the Loreto API and receive production-ready skill packages, complete with SKILL.md, test scripts, and reference stubs.

Transcribe and summarize video content from links using various transcription services.

AI-powered music production in REAPER via the Model Context Protocol — 150 tools for composition, mixing, mastering, and audio analysis.

Cinema-grade video production MCP server — 8 tools for recording, editing, effects, captions, TTS, and smart screenshots. Built on ffmpeg + Playwright.

: MCP server for AI media generation (imagesflux, videosveo3.1, music suno v5, with deterministic cost control using reserve-burn-refund billing

Create AI music videos and audio-reactive visuals from songs through MCP.

No reviews yet — be the first

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Install

More like this

Sequential Thinking

Time

Filesystem

EverArt

Google Maps

Google Drive