MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
作者による説明(英語の原文)
Lets an AI agent edit vertical 9:16 video ads from your footage, a reference ad or an idea.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"adanvil": {
"command": "uvx",
"args": [
"adanvil",
"mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add adanvil -- uvx adanvil mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"adanvil": {
"command": "uvx",
"args": [
"adanvil",
"mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"adanvil": {
"type": "stdio",
"command": "uvx",
"args": [
"adanvil",
"mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント maxbuildog で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.4.0)がレジストリに届いたのは18 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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
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