lipdub-mcp
OfficialLipDub MCP server
あなたのAIエージェントに、ビデオのリップシンク機能を与えます。
LipDub 2 は、ビデオ内の人物が、唇の動きを合わせて別の音声トラックを話しているように見せます。これは、その機能を Claude、Cursor、Gemini CLI、Codex、VS Code、その他のMCP互換クライアントに公開するMCPサーバーです。
LipDub 2 は翻訳、文字起こし、音声生成を行いません。 音声はご自身で用意してください。 ビデオを別の言語に吹き替えたい場合は、まずテキスト読み上げや音声クローン作成ツールで音声を生成し、公開 URL でホストして、その URL を渡してください。 このサーバーは TTS サーバーと組み合わせて使うことを意図しています。それが想定されたワークフローです。
動作のようす
You: Lip-sync https://example.com/keynote.mp4 to https://example.com/spanish.mp3
Claude: I'll use LipDub 2 for that. This will charge credits to your LipDub
account and can't be refunded — shall I go ahead?
You: yes
Claude: Started — render_id rnd_88213. This usually takes 7–15 minutes; I'll wait.
...
Done. Here's your video: https://… (link expires, so grab it soon)Related MCP server: atsurae
セットアップ
1. APIキーを取得する
app.lipdub.ai にサインインします。
Settings → API Keys を開く: app.lipdub.ai/settings/api-keys
この操作を行うには、アカウント上で Owner または Admin のロールが必要です。それ以外のロールは説明もなくダッシュボードへリダイレクトされます。そのリンクが通らない場合は、チームの Owner または Admin にキーを生成してもらってください。
キーを生成し、コピーします。
ユーザーごとに1つのキー。 LipDub はユーザーごとにAPIキーを1つだけ発行し、新しいキーを生成すると古いキーは置き換えられます。お使いのアカウントがすでにそのキーを別の連携で使っている場合、新しいキーを生成するとその連携が壊れます。既存のキーを使い回すか、エージェント作業専用の革 Owner/Admin アカウントを作成してください。
2. サーバーを追加する
まだ npm には公開されていません。 下の
npxコマンドは、パッケージが公開された後に動くようになるものです。それまでは、このセクション末尾の「ソースから」オプションを使用してください。動作は同じです。
claude mcp add lipdub --env LIPDUB_API_KEY=your_key_here -- npx -y lipdub-mcp{
"mcpServers": {
"lipdub": {
"command": "npx",
"args": ["-y", "lipdub-mcp"],
"env": { "LIPDUB_API_KEY": "your_key_here" }
}
}
}{
"mcpServers": {
"lipdub": {
"command": "npx",
"args": ["-y", "lipdub-mcp"],
"env": { "LIPDUB_API_KEY": "your_key_here" }
}
}
}{
"inputs": [
{ "type": "promptString", "id": "lipdub-key", "description": "LipDub API Key", "password": true }
],
"servers": {
"lipdub": {
"command": "npx",
"args": ["-y", "lipdub-mcp"],
"env": { "LIPDUB_API_KEY": "${input:lipdub-key}" }
}
}
}このパターンは、コミットしてしまう可能性のあるファイルからキーを守ります。LipDub がユーザーごとに1つのキーを発行することを考えると、この措置は大半のサーバーよりも重要です。
{
"mcpServers": {
"lipdub": {
"command": "npx",
"args": ["-y", "lipdub-mcp"],
"env": { "LIPDUB_API_KEY": "your_key_here" }
}
}
}[mcp_servers.lipdub]
command = "npx"
args = ["-y", "lipdub-mcp"]
env = { LIPDUB_API_KEY = "your_key_here" }git clone https://github.com/marzvfx/lipdub-mcp.git
cd lipdub-mcp
npm ci && npm run build次に、クライアントをビルド済みのエントリーポイントへ向けて:
{
"mcpServers": {
"lipdub": {
"command": "node",
"args": ["/absolute/path/to/lipdub-mcp/dist/index.js"],
"env": { "LIPDUB_API_KEY": "your_key_here" }
}
}
}Node 20+ が必要です。Node をインストールしたくない場合でも、./manage.sh build を実行するとコンテナ内で同じ操作ができます。
3. 動作確認をする
エージェントに 「check my LipDub connection」 と尋ねてください。
サーバー単体でも簡単に確認できます:
npx lipdub-mcp --version # or: node dist/index.js --versionツール
ツール | 説明 | クレジットを消費するか |
| キーが機能することを確認し、アカウント名を表示する | いいえ |
| ビデオURLと音声URLからレンダリングを開始する | はい |
| ステータスと、完了後のダウンロードリンクを取得する | いいえ |
| ループでポーリングする代わりにレンダリングを待つ | いいえ |
| 最近のレンダリング一覧を取得し、紛失したレンダリングIDを復元する | いいえ |
また、lipdub_quick_dub プロンプト(プロンプト機能を持つクライアントではスラッシュコマンド)と、2つの参照リソース lipdub://guide/quickstart および lipdub://guide/troubleshooting があります。
良いソースビデオの条件
カメラに映っているのは1人であること。
顔がはっきり見え、十分な明るさがあること。
ビデオ:
.mp4,.mov,.avi,.webm。音声:.mp3,.wav,.m4a,.aac。
ファイルのホステイング
両方の入力は公開URLです。ローカルファイルのパスではありません。リンクはメディアファイルそのものを返す必要があります。
次は機能しません: Google Drive、Dropbox、YouTube の共有ページ、ログインが必要なもの、期限切れのリンク。
機能するもの:
# Amazon S3 — a time-limited direct link
aws s3 presign s3://your-bucket/keynote.mp4 --expires-in 3600
# Google Cloud Storage
gcloud storage sign-url gs://your-bucket/keynote.mp4 --duration=1h
# Any web server
scp keynote.mp4 you@yourserver:/var/www/html/
# → https://yourserver/keynote.mp4なぜローカルファイルではなくURLなのか? URLベースのレンダリングはAPI呼び出し1回で完了します。ローカルファイルのアップロードは、1時間あたり約10リクエストにレート制限されているエンドポイントに対して複数回の呼び出しが必要で、エントリープランでは1時間あたり約2件のレンダリングになってしまいます。このサーバーをURL専用にすると、どの環境で実行しても同じ動作になります。ローカルファイル対応は、後にオプトインとして追加されるかもしれません。
処理時間とコスト
レンダリングには約 7~15分 かかります。レンダリングは LipDub アカウントのクレジットを消費し、払い戻しはできません。コストはソースビデオの長さに応じて変動するため、短いクリップほど安価です。
ステータスの確認は無料でレート制限もありません。ポーリングは何度でも行えます。
クレジット残高はAPIからは取得できません。app.lipdub.ai で確認してください。
コストの安全措置
lipdub_create_render は、クレジットを消費する唯一のツールです。デフォルトでは、エージェントが confirm_spend を渡すまでは実行を拒否し、最初にコストを明示することを強制します。サーバーはセッションあたり5件のレンダリング後に停止します。
変数 | デフォルト | 説明 |
| — | APIキー。必須です。 |
| — | 変数ではなく、キーを書いたファイルのパス。 |
|
| サーバープロセスあたりレンダリングを開始できる上限。 |
|
| 人間が確認するヘッドレスパイプラインでのみ |
|
|
|
これらは安全性というよりはユーザビリティのためのものです。API を直接呼び出してしまえば、すべて回避できます。
トラブルシューティング
症状 | 対処法 |
"No LipDub API key" | Settings → API Keys でキーを生成し、 |
"LipDub rejected" | キーが打ち間違っているか、生成済みです。新しいキーを生成し、クライアントを再起動してください。 |
"fire or "out of credits" | app.lipdub.ai でチャージします。 |
"could not download one of the source files" | リンクが共有ページ、ログイン必須、または期限切れです。直接リンクを使用してください。 |
"downloaded your files but could not start the render" | 通常は、クレジット不足か、はっきり見える顔がないことが原因です。 |
Wait tool returned | 正常です。レンダリングは7–15分かかるため、もう一度呼び出してください。 |
Download link stopped working | リンクは署名付きで短時間だけ有効です。再度 |
完全なAPIドキュメント: lipdub.readme.io
プライバシー
APIキーは環境から読み取られ、
https://api.lipdub.aiのポート呼び出しにのみ使用されます。ディスクに書き込まれたり、ログに記録されたり、ツールの結果として公開されることはありません。すべてのログプロックとエラーメッセージにマスクされます。指定したビデオURLと音声URLは LipDub API に送信され、その URL をダウンロードしてレンダリングを生成します。LipDub に処理されてもよい素材のURLだけを渡してください。
このサーバーはテレメトリーを送信せず、アナリティクスも集計しません。
レンダリングとその結果はあなたの LipDub アカウントに保存され、LipDub のプライバシーポリシーと利用規約によることがあります。
許容されない利用
LipDub 2 は実在の人物の合成ビデオを生み出します。このサーバーを使うことで、あなたがソース素材の表情とその音声に必要な権利と同意を持っていることを保証することになります。本人の許可なくなりすましたり、実在の人物について誤解させるコンテンツを作成したり、LipDub の規約で禁止されている行為に使用することはできません。
セキュリティ
脆弱性を発見しましたか? SECURITY.md を参照してください。セキュリティ問題を公開の issue で報告しないでください。また、API キーを issue に貼ることは絶対にしないでください。
制限事項
翻訳、音声生成はありません。音声はあなたが用意します。
URL 入力のみ対応。ローカルファイルのアップロードには対応していません。
クレジット残高や価格見積もりはAPIから取得できません。
LipDub はユーザーごとに1つのAPIキーを発行するため、当サーバーだけに限定してキーをスコープをすることはできません。
バージョニング
ツール名は公開API的な契約であり、変更されることはありません。新しい機能は新しいツールとして追加され、スキーマ変更は後方互換的に行われます。CHANGELOG.md を参照してください。
ライセンス
MIT。このライセンスは本クライアントにのみ適用されます。LipDub それ自身は独自の規約で提供される商業サービスです。
Available Tools
5 toolslipdub_check_connectionCheck LipDub connectionARead-onlyIdempotent
Verify that this server can reach LipDub and report which account it is using.
Call this first if any other LipDub tool fails with an authentication error, or when a user asks whether LipDub is set up.
Does not use credits and does not start anything.
Credit balance is not available through the API — direct the user to https://app.lipdub.ai to see it.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive, but the description goes further: it states that the tool does not use credits and does not start anything, and it discloses that credit balance is not available via the API, directing users to the web app. These are behavioral details beyond what annotations capture, providing real value for an agent deciding whether to call it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short paragraphs, each with a distinct purpose: purpose, when to use, and notes. Every sentence earns its place with no filler. The key purpose is front-loaded, and the caveats are placed last without bloating the text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter health-check tool with no output schema, the description fully covers what an agent needs: what it does, when to use it, what it doesn't affect, and an important limitation (credit balance). The sibling tools are all about renders, so this check tool is clearly distinct. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is nothing to describe. The schema coverage is trivially 100%. Per the baseline rule, a score of 4 is appropriate because the description adds no parameter-specific info, but none is needed. The description correctly avoids inventing unnecessary parameter explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a concrete verb+resource: 'Verify that this server can reach LipDub and report which account it is using.' This is unambiguous and clearly distinguishes it from the sibling render-management tools. Even without seeing the siblings, the tool's role is immediately understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to call it: 'Call this first if any other LipDub tool fails with an authentication error, or when a user asks whether LipDub is set up.' It also clarifies what it does NOT do (uses credits, starts anything), which prevents misuse. This is textbook usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lipdub_create_renderCreate LipDub render (uses account credits)A
Start a LipDub 2 render: make the person in a source video appear to speak a different audio track, with matched lip movement.
USES CREDITS. Each render charges the account and cannot be undone or refunded. Cost scales with the length of the source video. Confirm with the user first, then call again with confirm_spend set to true.
Supply both sides as direct, publicly downloadable URLs:
video_url — a video of ONE person speaking, face clearly visible.
audio_url — the audio you want them to appear to say.
LipDub 2 does NOT translate, transcribe or generate speech. If the user wants another language, produce that audio first with a separate text-to-speech or voice tool, host it at a URL, and pass that URL as audio_url.
Links must return the media file itself, with two exceptions: YouTube links work (youtube.com, youtu.be or youtube-nocookie.com), because they are resolved for you. Google Drive and Dropbox share pages, and anything behind a login, will fail.
Returns immediately with a render_id — the render is NOT finished. Rendering takes several minutes for a short clip, and longer for longer videos. Next step: call lipdub_wait_for_render with that render_id.
| Name | Required | Description | Default |
|---|---|---|---|
| audio_id | No | Advanced. A LipDub audio upload id from a previous upload, instead of audio_url. | |
| video_id | No | Advanced. A LipDub shot id from a previous upload, instead of video_url. | |
| audio_url | No | Direct URL to the audio the person should appear to say (.mp3, .wav, .m4a, .aac, .ogg, .flac, .mp4 or .mov). You must supply finished audio; LipDub 2 does not generate or translate speech. | |
| video_url | No | URL to the source video (one person, face visible). .mp4, .mov or .avi, or a YouTube link. | |
| callback_url | No | Optional https URL to be called when the render finishes. For automated pipelines; in a chat session use lipdub_wait_for_render instead. | |
| confirm_spend | No | Whether the user has personally approved spending credits on this render. Defaults to false deliberately, as a safety gate — it is not a misconfiguration. Set it to true only after you have asked the user and they have agreed. Setting it yourself without asking spends their money without consent. | |
| output_filename | No | Optional name for the finished file, e.g. 'ceo-welcome-spanish.mp4'. If omitted, a name is derived from video_url. This name is also shown as the project name in the user's LipDub web app, so make it meaningful. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes well beyond the annotations by disclosing financial consequences ('USES CREDITS', 'cannot be undone or refunded'), cost scaling with source video length, asynchronous behavior (returns render_id immediately, render not finished), and typical render duration. No contradiction with the annotations; this description adds substantial behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the most critical information (purpose and cost warning), then organized into clear paragraphs and bullet lists covering inputs, exclusions, and post-call behavior. Every sentence earns its place; the length is justified by the tool's high-stakes, asynchronous, and easily-misused nature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description fully explains what the caller should expect: an immediate render_id, that rendering is asynchronous, how long it may take, and the required next step. It also covers prerequisites, URL constraints, known failure modes, and the spending-confirmation gate, making it complete for correct invocation despite the schema listing all parameters as optional.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though schema coverage is 100%, the description adds crucial meaning: URLs must be direct, publicly downloadable media files; YouTube links are resolved but Google Drive/Dropbox share pages and login-protected links fail; video must show one person with a clear face; audio must be finished because LipDub does not generate speech. This meaningfully enriches the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Start a LipDub 2 render') and a clear resource with the intended effect: making the person in a source video appear to speak a different audio track with matched lip movement. This clearly distinguishes it from siblings like lipdub_list_renders, lipdub_get_render, and lipdub_wait_for_render, none of which create a render.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use and when-not-to-use guidance: confirms credits must be approved by the user first, instructs to call again with confirm_spend=true, warns that LipDub 2 does not translate/transcribe/generate speech, and routes follow-up to lipdub_wait_for_render. It also explains when callback_url is appropriate versus chat-session use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lipdub_get_renderCheck LipDub render statusARead-onlyIdempotent
Check a LipDub render once, right now, and return its download link if it has finished. This does NOT wait — it answers immediately with whatever the current status is. To wait for a render to finish, use lipdub_wait_for_render instead.
Takes the render_id from lipdub_create_render.
Free and never rate-limited — check as often as you need.
status is one of:
preparing — LipDub is downloading your source files (usually under 2 minutes)
queued — waiting for a render slot
rendering — generating the video
succeeded — done; download_url is included
failed — see failure_reason
download_url is a temporary signed link that expires. Give it to the user or download it promptly; do not save it for later.
If the render is not finished yet, prefer lipdub_wait_for_render — it waits for you instead of making you check repeatedly.
| Name | Required | Description | Default |
|---|---|---|---|
| render_id | Yes | The render_id from lipdub_create_render. A plain number is also accepted. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnlyHint and idempotentHint, and the description layers genuinely useful context on top: the immediate-non-waiting behavior, the full status enum with meanings, and the critical caveat that download_url is a temporary signed link that must be handed to the user or downloaded promptly. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core single-check purpose and the critical non-waiting distinction, followed by usage, rate limits, status enum, and URL handling in logical order. It is slightly verbose — the status enum and expiry caveat could theoretically live in an output schema — but every section earns its place with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description covers everything an agent needs: the status value set, what download_url contains and its expiry behavior, how render_id is obtained, and routing to the wait sibling. Nothing required for a correct call is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already documents render_id thoroughly ('The render_id from lipdub_create_render. A plain number is also accepted.'). The description just restates the source ('Takes the render_id from lipdub_create_render'), adding little beyond the schema. Baseline 3 is appropriate since the schema carries the load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise verb-resource pair — 'Check a LipDub render once, right now' — and distinguishes itself from lipdub_wait_for_render by clarifying what it does NOT do ('does NOT wait'). This makes it trivially distinguishable from its siblings without opening any schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit when-to-use and when-not-to-use guidance is given in two places: 'To wait for a render to finish, use lipdub_wait_for_render instead' and the closing 'If the render is not finished yet, prefer lipdub_wait_for_render'. It also states the unthrottled nature ('Free and never rate-limited — check as often as you need'), giving the agent a clear green light for polling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lipdub_list_rendersList recent LipDub rendersARead-onlyIdempotent
List recent LipDub renders on this account, newest first.
Use this when:
you have lost a render_id, for example because earlier conversation was trimmed away and a render is still running or already finished
the user asks what they have rendered recently
Returns a short summary of each. Call lipdub_get_render with one of the returned render_ids to get its download link.
Free and never rate-limited.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many renders to return. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable context: it is account-scoped, returns 'a short summary of each', and is 'Free and never rate-limited'. This goes beyond the annotations by disclosing cost and rate-limit behavior, which is genuinely useful for an agent deciding whether to call it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear main statement, bullet-pointed 'when to use' triggers, and a note about returns and cost. It is slightly longer than strictly necessary, but every section serves a purpose and no sentence is wasted. The main action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one optional parameter and no output schema, the description covers the essential information: what it returns (short summary), how to proceed to get a download link (via lipdub_get_render), and cost/free status. It does not describe the exact shape of the summary, but that is not critical for invoking the tool. Overall it is sufficient for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'limit' is fully documented in the input schema (type, default, min, max, description). The tool description adds no additional semantics beyond the schema — it does not mention pagination limits or default behavior. With 100% schema coverage, the baseline of 3 is appropriate; the description does not need to repeat schema details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('List'), a resource ('LipDub renders'), and a scope ('on this account'), plus an explicit ordering ('newest first'). It clearly distinguishes from siblings like lipdub_get_render (retrieve one) or lipdub_create_render (make new), so an agent can immediately identify the tool's role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit 'Use this when' conditions: losing a render_id (e.g., after conversation trimming) or when the user asks for recent renders. It also advises the follow-up call to lipdub_get_render, giving clear decision guidance about when this tool is appropriate and what to do next.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lipdub_wait_for_renderWait for LipDub render to finishARead-onlyIdempotent
Wait for a LipDub render to finish, then return its download link. Use this straight after lipdub_create_render instead of checking in a loop — it uses far less context.
This call blocks for up to max_wait_seconds (default 45, maximum 600) while tracking the render for you. A render takes several minutes for a short clip, and longer for longer videos, so expect to call this several times — that is normal and costs nothing.
If the render is still going when the wait is up, this returns normally with still_running set to true. That is NOT an error and NOT a failure — the render is fine and is still going. When it happens: tell the user it is still in progress, give them the render_id so they can come back to it, and call this tool again to keep waiting.
Waiting and status checks are free and never rate-limited.
| Name | Required | Description | Default |
|---|---|---|---|
| render_id | Yes | The render_id from lipdub_create_render. | |
| max_wait_seconds | No | How long to wait before returning. Returning early with still_running set to true is normal, not a failure. The default of 45 stays under the 60-second request timeout most MCP clients use; only raise it if your client is configured to wait longer. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, but the description adds critical behavioral detail beyond these: the blocking nature, the max_wait_seconds cap, the normal return with still_running, and the explicit statement that it is not an error. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently organized: purpose first, then usage, then behavior, then user guidance. Every sentence earns its place—no fluff. It front-loads the core purpose and the key differentiator, and the length is appropriate for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully covers what an agent needs: how to call it, what to expect (including partial results), how to handle still_running, and cost/rate-limit implications. It leaves no gaps for correct invocation and follow-up.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters documented). The description adds context beyond the schema, such as explaining that renders take several minutes and it's normal to call repeatedly, which informs how to set max_wait_seconds. However, the schema already covers the key semantics of max_wait_seconds and still_running, so the description's extra value is limited but present.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a precise verb-resource pair: 'Wait for a LipDub render to finish, then return its download link.' It explicitly differentiates from alternatives by stating to use it 'straight after lipdub_create_render instead of checking in a loop,' making the tool's purpose unambiguous and distinct from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when-to-use guidance: 'Use this straight after lipdub_create_render instead of checking in a loop.' It also instructs what to do when still_running is true: tell the user, provide the render_id, and call again. It even notes that repeated calls are normal and free, covering both timing and cost expectations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v0.1.1- Changed
lipdub_create_render3 fields changed- changed
Input schema / properties / audio_url / descriptionPrevious value: -"Direct https URL to the audio the person should appear to say. You must supply finished audio; LipDub 2 does not generate or translate speech."New value: +"Direct URL to the audio the person should appear to say (.mp3, .wav, .m4a, .aac, .ogg, .flac, .mp4 or .mov). You must supply finished audio; LipDub 2 does not generate or translate speech." - removed
Input schema / properties / transcriptRemoved value: -{ - "description": "Optional. The words spoken in audio_url. Supplying this can improve lip-sync accuracy.", - "maxLength": 4096, - "type": "string" -} - changed
Input schema / properties / video_url / descriptionPrevious value: -"Direct https URL to the source video (one person, face visible). .mp4, .mov, .avi or .webm."New value: +"URL to the source video (one person, face visible). .mp4, .mov or .avi, or a YouTube link."
- Changed
lipdub_wait_for_render2 fields changed- changed
Input schema / properties / max_wait_seconds / defaultPrevious value: -240New value: +45 - changed
Input schema / properties / max_wait_seconds / descriptionPrevious value: -"How long to wait before returning. Returning early with still_running set to true is normal, not a failure."New value: +"How long to wait before returning. Returning early with still_running set to true is normal, not a failure. The default of 45 stays under the 60-second request timeout most MCP clients use; only raise it if your client is configured to wait longer."
5 tool updates
v0.1.0- First observed
lipdub_check_connection - First observed
lipdub_create_render - First observed
lipdub_get_render - First observed
lipdub_list_renders - First observed
lipdub_wait_for_render
TDQS
Scored across 5 tools
Each tool has a clearly distinct role: connection check, listing, creating, one-shot status check, and blocking wait. The overlap between get_render and wait_for_render is explicitly disambiguated in their descriptions.
All tools follow the same lipdub_ prefix with a consistent verb_noun pattern: check_connection, list_renders, create_render, get_render, wait_for_render. There are no naming style deviations.
Five tools is well-scoped for this server's purpose. Each tool covers a necessary part of the render workflow without redundancy or bloat.
The tool surface covers the full render lifecycle: verify setup, create a render, wait for completion, retrieve the result, and list past renders. No obvious missing operation is needed for the stated domain.
Maintenance
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