Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者による説明(英語の原文)
Compose and render video from one JSON template. Deterministic, runs locally, no generative model.
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。
LECLAP_MCP_OUTPUT_DIR, LECLAP_MCP_MEDIA_DIR, LECLAP_MCP_RENDER_TIMEOUT_MS, LECLAP_MCP_ALLOW_REMOTION, LECLAP_MCP_REMOTION_ENTRY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": {
"video": {
"command": "npx",
"args": [
"-y",
"@leclap/mcp"
],
"env": {
"LECLAP_MCP_OUTPUT_DIR": "your-value",
"LECLAP_MCP_MEDIA_DIR": "your-value",
"LECLAP_MCP_RENDER_TIMEOUT_MS": "your-value",
"LECLAP_MCP_ALLOW_REMOTION": "your-value",
"LECLAP_MCP_REMOTION_ENTRY": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add video --env LECLAP_MCP_OUTPUT_DIR=your-value --env LECLAP_MCP_MEDIA_DIR=your-value --env LECLAP_MCP_RENDER_TIMEOUT_MS=your-value --env LECLAP_MCP_ALLOW_REMOTION=your-value --env LECLAP_MCP_REMOTION_ENTRY=your-value -- npx -y @leclap/mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"video": {
"command": "npx",
"args": [
"-y",
"@leclap/mcp"
],
"env": {
"LECLAP_MCP_OUTPUT_DIR": "your-value",
"LECLAP_MCP_MEDIA_DIR": "your-value",
"LECLAP_MCP_RENDER_TIMEOUT_MS": "your-value",
"LECLAP_MCP_ALLOW_REMOTION": "your-value",
"LECLAP_MCP_REMOTION_ENTRY": "your-value"
}
}
}
}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": {
"video": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@leclap/mcp"
],
"env": {
"LECLAP_MCP_OUTPUT_DIR": "your-value",
"LECLAP_MCP_MEDIA_DIR": "your-value",
"LECLAP_MCP_RENDER_TIMEOUT_MS": "your-value",
"LECLAP_MCP_ALLOW_REMOTION": "your-value",
"LECLAP_MCP_REMOTION_ENTRY": "your-value"
}
}
}
}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。
LECLAP_MCP_OUTPUT_DIR envLECLAP_MCP_MEDIA_DIR envLECLAP_MCP_RENDER_TIMEOUT_MS envLECLAP_MCP_ALLOW_REMOTION envLECLAP_MCP_REMOTION_ENTRY env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6日にチェック
レジストリ名はドメイン leclap.dev で確認済みです(レジストリがドメインの所有を確認しています)
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(0.3.4)がレジストリに届いたのは2 か月前です。
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Node.jsも必要です。
同じカテゴリには:Figma Context MCP, Claude Real Video, Figma MCP Server
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
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
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。
Connect your AI agent to LeClap’s video engine. Discover samples, author a template, validate it, inspect real frames, revise and render. Start with the agent guide.
An MCP server that exposes the ffmpeg-video-composer engine as agent-callable video tools.
An AI agent (Claude Desktop, Cursor, …) is the LLM; this server helps it author a customized template with nice effects from the schema, then validates and renders it deterministically to an mp4. The server includes the 50 showcase samples through the shared packaged catalog, with creative direction, descriptors and required inputs. It works without the app or private creative-kit at runtime. Remotion-assisted authoring is an optional path. The result is _agent-composable, deterministic, reproducible_ video — the opposite of generative video models, which sample rather than render.
| Tool | Description |
|---|---|
get_samples | Without id: sample metadata and required inputs, filtered by category/backend/query → { samples }; with id: that sample with its self-contained template JSON |
get_template_schema | The JSON Schema for a template descriptor + a short authoring guide |
get_motion_catalog | Motion presets, camera, graphics, transitions, easing/time grammar, themes, platforms, genre doctrine and scene blueprints; { query, kind? } → ranked matches (a query matching nothing is logged to the catalog gap log) |
validate_template | Dry-run an inline descriptor (no render) → { valid, sectionCount, orientation, requiredClips, formFields, fields?, geometry?, featureWarnings? }; include: ["resolved"] adds resolved (the descriptor for fields/format), include: ["timeline"] adds timeline (sections, motion events, beats, cues) |
compose_video | Validate an inline descriptor and render (one format of it, optionally) → { outputPath, durationSeconds, sizeBytes, videoCodec, audioCodec, renderId }, plus a resource_link to the mp4 |
render_frames | Render a native template and return still frames as PNG images + paths: at, atTransitions, perSection, sheet, safe, zoom, variants, looks |
edit_template | JSON Patch operations and/or registered effectProps by section name over inline JSON, under expectedRevision, all-or-nothing → { template, revision, changedPaths, changedSections? } |
probe_media | Inspect a local media file → codecs, duration, sample rate, size, and HDR / colour / bit depth / VFR / rotation traits |
extract_style | Reference image/clip under the media dir → { theme, styleGuide, confidence }: palette roles + WCAG contrast, grain, pacing (palette and pacing only) |
extract_structure | A reference clip's format (shots, rhythm, transitions, grounds, layout) as binding rules for a template. Format only; samples every 0.25 s for up to 2 minutes. |
extract_brand | A website's brand kit (name, colours, fonts, logo) as a theme and binding rules, saved under /brand-kits/ /. Needs --allow-network. |
analyze_music | Measure a local music file → { bpm, offset, beatsPerBar, confidence, usable, cues, globalBeats } for global.beats and cue:drop |
analyze_sound | Render an sfx[].sound (composed, or a preset with variations) → length, peak/RMS dBFS, centroid, high/low energy shares, attack, advisories + spectrogram and waveform PNGs |
transcribe_media | Transcribe a local audio/video file's speech with whisper.cpp, locally → { words, srt, language, confidence, advice } to pin into subtitles.words |
get_capabilities | Local FFmpeg capability report (listings + one-frame probes) → each feature yes/no/unknown with a fix |
open_in_builder | Template → a leclap.dev/studio/builder#t=… link for a person to edit it; the template rides in the URL fragment (never sent to a server) → { url, length, mediaToRebind, warnings } |
render_remotion_clip | _(bonus, opt-in)_ Render a composition from your own Remotion project → an mp4 clip for a project_video section |
analyze_sound seeds a sound's noise and jitter with seed (default 0). To hear the exact render a template will play, pass the template's global.seed as seed and the cue's path as cue: "sections.intro.sfx[0]" for the first cue of the section named intro, "global.sfx[2]" for the third global cue. The tool then seeds the sound as the mix seeds that cue and returns the seed it used. Levels are floored at -120 dBFS, so a silent sound reads -120 and raises sound_silent.
Typical agent flow: get_samples → get_samples { id } → inspect requirements and customize media/copy → get_template_schema → validate_template (iterate until valid) → render_frames (look at the result; check safe zones with safe) → compose_video → read the returned outputPath. Author a fresh descriptor from the schema when no sample fits.
render_frames renders through a per-section cache under /.section-cache, so a second look after a small edit re-encodes only the sections that changed. It runs in the render worker under the same media-dir checks, slot cap, timeout and cancellation as compose_video, writes PNGs to /frames- /, and inlines at most eight images (the sheets when sheet is set). Moments are seconds or time references on the whole video: "intro.end" (a section or an element id), "50%", "beat:8", "cue:drop + 0.1". validate_template with include: ["timeline"] lists the moments worth picking.
validate_template also reports, render-free, text that would run off the frame or out of title-safe, collide with other text, sit under a band, be too small, lack contrast, or sit over footage with no box, outline or shadow. Those findings arrive on the optional geometry field — one line each, saying what to change, and the field is absent entirely when there is nothing to fix. They are advisory: valid stays true. A line ending (approx: …) says why it is an estimate: the font could not be read, the text carries a {{ variable }} that only resolves at render time, or a section declares no duration. When a font is not bundled, the server fetches it from the LeClap asset catalog (5s timeout); offline, it estimates.
Pass render: true to validate_template to also render the sections that hold text and measure their contrast from real pixels — it settles text over images, grades and looks that the render-free check can only call unknown. It costs seconds (two renders of those sections), goes through the same media-dir sandbox as compose_video, reads assets from the media dir, and runs in the same forked render worker under the same timeout. It adds a render field (measured, seconds, and unavailable when it could not render — no FFmpeg with drawtext, a failed render, or a timeout); the render-free findings come back either way.
get_samples is always available, even with Remotion disabled. It reads packaged data only: no media downloads, effect execution or repository access. Without id it lists, filtered by optional category (templates, typography, effects, app-demos, overlays, evidence), backend (native, remotion) and case-insensitive query (up to 4000 characters). With id (1–200 characters) it returns that sample.
{ "name": "get_samples", "arguments": { "category": "app-demos", "backend": "native" } }
{ "name": "get_samples", "arguments": { "id": "web-app-promo" } }
Results include identical JSON in text and structuredContent; with id, the descriptor sits at template alongside its metadata. Unknown IDs return isError with a discovery hint. Required inputs include named clips and durations/capture hints, form fields and limits, variables/defaults/placeholders, assets, effective preset font files (source: "preset") and versioned effects. Replace the sample copy, supply clips by userVideoPaths and form values by fields, customize global.variables, then pass template to validate_template and compose_video. Referenced partials are embedded in the descriptor.
The 25 native samples use FFmpeg; the 10 registered effect samples require --allow-remotion, Remotion peers and a trusted --remotion-entry. Effects with customCatalog: true also require the operator's --effect-catalog and the matching composition in that entry. Sample discovery does not enable execution, install a catalog or supply React source. Inspect requirements.setup and, after operator setup, get_effect_schema before editing effect props. See operator catalogs.
Pr
冒頭だけを表示しています。続きはリポジトリで読めます