MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Lets an AI agent edit vertical 9:16 video ads from your footage, a reference ad or an idea.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"adanvil": {
"command": "uvx",
"args": [
"adanvil",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add adanvil -- uvx adanvil mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"adanvil": {
"command": "uvx",
"args": [
"adanvil",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"adanvil": {
"type": "stdio",
"command": "uvx",
"args": [
"adanvil",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 maxbuildog 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.4.0)은 18일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
An MCP server that lets an AI agent edit vertical 9:16 video ads.
AdAnvil works with Claude Code, Codex, Cursor or any MCP client. It builds ads from a brand's own footage, from a reference ad, or from an idea. The agent judges (which clips, what the text says, whether the result looks right). AdAnvil renders deterministically and checks the result: the same storyboard always gives the same video.
It is not tied to a niche. The recipes and the editing guide speak in general terms (product, benefit, problem, target customer) with examples from several niches: coffee, fashion, fitness, pets, software, home, beauty.
The demo above was made from the CC0 demo pack in examples/demo/ (four Wikimedia Commons clips, a product still and a fictional brand called Ember & Oak). No footage is stored in this repository: the pack is fetched on demand.
pill, meme, outline, outline_soft, box, label, comment) with emoji support.start/end windows; a sentence end the voice repeats is cut and flagged.sfx overlays and audio.sfx_auto at the cuts and captions, and cuts that snap to the beat of the music.story: "offer") for announcements and lead-collection ads that show the product from the first second.Pick one path. The first is the simplest.
Download adanvil- .mcpb from the latest release, double-click it, and click Install in Claude Desktop. It asks for a projects folder and, optionally, a Freesound key (stored securely). You still need ffmpeg 6.1 or newer on your computer (brew install ffmpeg, winget install Gyan.FFmpeg, sudo apt install ffmpeg); if it is missing, the extension says so with the command for your system.
git clone https://github.com/maxbuildog/adanvil && cd adanvil
docker build -t adanvil .
The image has ffmpeg 6.1, runs as a non-root user and speaks MCP over stdio. Mount the folder that holds your projects at /projects; the agent must give tool calls paths under /projects (for example /projects/my-ad): the image sets ADANVIL_PROJECTS_DIR=/projects, so any other folder, and /projects itself, is refused.
# Claude Code
claude mcp add adanvil -- docker run -i --rm -v "$PWD:/projects" adanvil
On Linux add --user "$(id -u):$(id -g)" so the files written to the folder belong to you.
Codex, in ~/.codex/config.toml:
[mcp_servers.adanvil]
command = "docker" args = ["run", "-i", "--rm", "-v", "/home/you/ads:/projects", "adanvil"] tool_timeout_sec = 900 default_tools_approval_mode = "approve" # needed with approval_policy = "never" (codex exec)
Cursor, in .cursor/mcp.json:
{
"mcpServers": { "adanvil": { "command": "docker", "args": ["run", "-i", "--rm", "-v", "/home/you/ads:/projects", "adanvil"] } } }
The image holds the base package only. Transcription is available with docker build --build-arg EXTRAS=transcribe -t adanvil:transcribe .. The voice, vision and music-generation environments (adanvil voice-setup, vision_setup, music-setup) are not included: they need gigabytes of models, so use the uvx path for them.
Requirements: Python 3.11 or newer, uv (it provides uvx), and ffmpeg 6.1 or newer, built with libzimg, on your PATH (check with ffmpeg -version; if it lives elsewhere, set ADANVIL_FFMPEG and ADANVIL_FFPROBE to the full paths).
# 1. Check the install (the first run downloads the package)
uvx --from adanvil adanvil --version
claude mcp add adanvil -e ADANVIL_PROJECTS_DIR="$HOME/AdAnvil" -- uvx --from adanvil adanvil-mcp
ADANVIL_PROJECTS_DIR (recommended) is the folder that holds your projects: the server then refuses any project outside it. Projects are subfolders of it (for example ~/AdAnvil/summer-ad). See SECURITY.md.
The package is named adanvil. It installs two commands: adanvil (command line) and adanvil-mcp (the MCP server over stdio). uvx adanvil-mcp alone does not work, because uvx looks for a package with that name: always add --from.
The agent creates the project folder and tells you where to drop your files: footage in footage/, the reference ad in reference/, music in music/, logo and end card in brand/. It learns the method from the editing_guide tool and from AGENTS.md.
Codex, in ~/.codex/config.toml:
[mcp_servers.adanvil]
command = "uvx" args = ["--from", "adanvil", "adanvil-mcp"] env = { ADANVIL_PROJECTS_DIR = "/home/you/AdAnvil" } tool_timeout_sec = 900 # indexing long footage can take minutes default_tools_approval_mode = "approve" # needed with approval_policy = "never" (codex exec)
Without default_tools_approval_mode, a non-interactive codex exec run rejects every AdAnvil tool call with "MCP tool call requires approval".
Cursor, in .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
{
"mcpServers": { "adanvil": { "command": "uvx", "args": ["--from", "adanvil", "adanvil-mcp"], "env": { "ADANVIL_PROJECTS_DIR": "/home/you/AdAnvil" } } } }
Any other MCP client (generic stdio entry):
{
"mcpServers": { "adanvil": { "type": "stdio", "command": "uvx", "args": ["--from", "adanvil", "adanvil-mcp"], "env": { "ADANVIL_PROJECTS_DIR": "/home/you/AdAnvil" } } } }
Restart the client after editing its config, then ask the agent to call recipe_list. Nine recipes means the server is connected.
Optional: reference transcription needs the transcribe extra (faster-whisper). Use --from "adanvil[transcribe]" in place of the plain --from value above.
The demo needs a checkout, because the fetch script lives in the repository:
git clone https://github.com/maxbuildog/adanvil
cd adanvil uv sync uv run python examples/demo/fetch_demo.py ./demo-project uv run adanvil index ./demo-project --source footage
Then register the MCP server and ask your agent to make an ad from ./demo-project (give it the absolute path), or follow the command line walkthrough in examples/demo/README.md.
Everything lives in one project folder: footage/, brand/, music/, reference/, renders/, cache/, plus adanvil.json, brand.yaml and catalog.json. Every tool takes the absolute project_dir; every other path is relative to it and cannot escape it.
storyboard_validate checks the storyboard against the recipe rules, then render_start renders it in the background.qc_run checks the file and returns control images that the agent looks at before delivering; ad_score scores its creative quality (aim for 80 or more).Details: docs/ARCHITECTURE.md for the pipeline, docs/EDITING_GUIDE.md for the editing doctrine, and AGENTS.md for the step-by-step guide an agent follows (same content as skill/SKILL.md, the Claude Code skill version).
The result depends on the model that drives AdAnvil. Reference analysis and shot choice are judgement work: use the strongest model you can (for example Claude Opus) for them. Smaller models execute the steps well, but they tend to copy the surface of a reference (same words, same shots) instead of rebuilding its logic for your brand.
| Tool | What it does |
|---|---|
project_init | Create an AdAnvil project skeleton. |
project_read_text | Read one of AdAnvil's own text files in the project (licence notes, JSON, YAML; at most 1 MB). |
brand_onboard | Read a brand's site, then write the brand profile from the answers. |
brand_get | Read the brand profile and brief. |
library_index | Index or refresh footage (long runs become detached jobs; refresh_shots measures the cuts again). |
library_view | One catalogue entry with its contact sheet. |
library_annotate | Save what the agent saw in a clip (description, people, emotion, quality, exclusion). |
library_search | Search the indexed footage by text (including what the clips say), tags, people, emotion, duration, or by sentence (query, with the vision environment). |
speech_view | Compact phrases (with flags), fillers, restarts and clean cut segments of one clip's speech. |
speech_takes | The best take of each line across several recordings of a script. |
speech_refine | Transcribe chosen clips again with a stronger model and the brand vocabulary (detached job). |
library_overview | Overview of the footage folders without indexing, plus a mosaic. |
frame_view | The full-resolution frame ON SCREEN at t (floor(t * fps), a t within 1 ms of a frame boundary is that frame) or at frame, with its exact time. |
reference_decode | Decode a reference video into shots, pacing, text, speech and sheets. |
reference_breakdown | Save the agent's shot-by-shot breakdown of the reference. |
recipe_list | List the ad recipes with purpose and duration. |
recipe_get | One full recipe with its rules and an example. |
editing_guide | The editing doctrine for footage, copy, rendering and QC. |
storyboard_schema | The JSON Schema of the storyboard. |
| storyboard_save | Save a storyboard as storyboards/ .json once; later tools take that
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요