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)
Video pipeline for AI agents: analyze with AI, transcode to MP4/HLS/DASH, edit, protect and deliver.
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。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://mcp.qencode.com/mcpターミナルでこれを実行します
claude mcp add --transport http qencode https://mcp.qencode.com/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": {
"qencode": {
"url": "https://mcp.qencode.com/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": {
"qencode": {
"type": "http",
"url": "https://mcp.qencode.com/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。
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:
https://mcp.qencode.com/mcpメニューの名前は、プランや時期によって少し違うことがあります。
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。
このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。
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
レジストリ名はドメイン qencode.com 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
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
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。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は–、最新バージョン(1.2.0)がレジストリに届いたのは17 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。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
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。
Model Context Protocol (MCP) server for the Qencode Transcoding API.
Connect any MCP-compatible AI client — Claude, Cursor, ChatGPT, Grok, Gemini — to your Qencode account and let it submit, monitor, and reason about transcoding jobs on your behalf.
Once your client is connected (see Connect a client), ask your agent in plain English:
Transcode
https://example.com/input.mp4as an HLS ladder at 1080/720/540/360. Put it in my R2 bucketvideos/demo/.
The agent picks the hls_abr recipe, fills in the per-rendition encoding params, submits via start_encode2_raw, and polls until the job is done.
There are no API keys to copy into client config — authentication is browser-based OAuth.
The connector uses standard OAuth 2.1 — no API keys in client config. On first use, your client opens a browser, you sign in to your Qencode portal account, pick a project, and approve the requested scopes. The client stores the token; subsequent calls are silent until the token expires.
Scopes the client should request at authorize time (published via Protected Resource Metadata):
| Scope | Purpose |
|---|---|
openid | OIDC identity |
profile | Display name |
email | Account email |
offline_access | Refresh token |
transcoding:read | get_job_status, list_jobs, docs tools |
transcoding:write | transcode_video, start_encode2_raw |
The RS enforces transcoding:read and transcoding:write on access tokens at the transport layer.
Your Qencode API keys never leave the portal. The MCP server derives a short-lived session token per request via an internal portal endpoint.
The same connector is deployed in two environments. Each has its own domains, accounts, projects, and credentials — sign in to the portal that matches the endpoint you connect to.
| Role | Production | QA (testing) |
|---|---|---|
| MCP endpoint (connect here) | https://mcp.qencode.com/mcp | https://mcp-qa.qencode.com/mcp |
| Portal (sign in / projects) | https://portal.qencode.com | https://portal-qa.qencode.com |
| Authorization server | https://auth.qencode.com | https://auth-qa.qencode.com |
| Qencode API | https://api.qencode.com | https://api-qa.qencode.com |
The instructions below use the production endpoint. To test against QA, swap in the QA URL and sign in at the QA portal.
Endpoint: https://mcp.qencode.com/mcp — same for every client below. Sign in to your Qencode account when the browser opens and approve access.
QA (internal testing): use
https://mcp-qa.qencode.com/mcpand sign in at the QA portal instead.
| Client | Where to add it | MCP URL / config |
|---|---|---|
| Claude (chat) | Message box → + → Connectors → Add connector | https://mcp.qencode.com/mcp |
| Claude Code | Terminal | claude mcp add --transport http qencode https://mcp.qencode.com/mcp |
| ChatGPT | Apps → search Qencode → Connect; or Developer Mode → Build app | Connector URL: https://mcp.qencode.com/mcp |
| Gemini | ~/.gemini/settings.json → mcpServers | "httpUrl": "https://mcp.qencode.com/mcp" — then /mcp auth qencode in the CLI |
| Cursor | Settings → Tools & MCP → New MCP Server (or ~/.cursor/mcp.json) | "url": "https://mcp.qencode.com/mcp" — restart Cursor after saving |
Cursor (mcp.json):
{
"mcpServers": { "qencode": { "url": "https://mcp.qencode.com/mcp" } } }
Gemini (settings.json):
{
"mcpServers": { "qencode": { "httpUrl": "https://mcp.qencode.com/mcp", "timeout": 30000, "trust": false } } }
Tip: sign in to portal.qencode.com in your browser before connecting — OAuth goes smoother.
Transcoding & jobs
| Tool | Description |
|---|---|
transcode_video | Submit a job from a source URL to one or more outputs. Convenience wrapper — auto-injects encoder_version: 2 (or 1 for VMAF) when omitted. |
start_encode2_raw | Escape hatch — submit a job with the full query JSON exactly as the Qencode API expects. |
get_job_status | One-shot status snapshot by task_token. |
get_job_status_detailed | Full, authoritative job status, including per-rendition progress and output details. |
list_jobs | Inline jobs card for the task_tokens of the current conversation — status badges, filters, expandable rows, output URLs. The card refreshes itself while any job is still running. |
fetch_job_result | Read the contents of a result file produced by an analysis job (transcript, VMAF report, metadata, categorization). |
wait_for_job | Deprecated. Returns immediately and points at list_jobs; kept so older conversations do not hit "tool not found". |
search_qencode_docs | Search the built-in knowledge base of recipes and reference docs. |
fetch_qencode_doc | Fetch the full content of a knowledge-base resource by qencode:// URI (tool-based counterpart to resources/read). |
Playback
| Tool | Description |
|---|---|
open_player | Render a playable result inline — progressive MP4/WebM or an HLS/DASH manifest. The server applies the calling host's sandbox policy, so which source origins are allowed depends on the client. |
refresh_jobs | The jobs card's own silent poll. Not meant to be called directly by an agent; it backs the card's auto-refresh and Refresh button. |
Media Storage
Bucket management and ingest for Qencode Media Storage. These ride the same OAuth grant as the transcoding tools — no extra scope and no re-consent.
| Tool | Description |
|---|---|
list_buckets | List the Media Storage buckets available to the account. |
create_bucket | Create a new bucket. Called only on an explicit request — not to satisfy a missing destination. |
list_objects | Browse the contents of a bucket. |
get_download_url | Return a time-limited download URL for an existing object. |
download_url_to_bucket | Server-side copy of a public URL into a bucket (ingest, no transcoding). |
The server ships a knowledge base of recipes and reference docs, exposed as MCP resources so the agent can fetch only what it needs. Notable URIs:
qencode://docs/best-practices — composition defaults the agent applies automaticallyqencode://docs/storage — destination compatibility matrix (Qencode S3, R2, AWS S3, Azure, B2, FTP/SFTP)qencode://docs/error-codes — error code → cause → fixqencode://docs/gotchas — non-obvious API quirksqencode://schema/digest — full attribute reference for start_encode2qencode://recipe/ — one per feature flow: ai_detection, ai_upscaling, audio_outputs, callbacks, clip_trim, codec_av1, codec_lcevc, drm_aes128, drm_buydrm, drm_doverunner, drm_expressplay, drm_fairplay_ezdrm, drm_forensic_watermark, drm_playready_ezdrm, drm_widevine_ezdrm, hdr_to_sdr, hls_abr, incremental_abr, mp4_ladder, per_title_encoding, refresh_abr_playlist, reliability, repack, rotate_deinterlace, smart_crop, smart_thumbnail, speech_to_text, stitching, subtitles, thumbnails, video_intelligence, video_metadata, vmaf_quality, vr_360, vr_mode, watermark_logo, waveformUse search_qencode_docs to discover the right recipe URI for a goal.
In clients that surface MCP prompts, 40 one-shot templates are available. Each tells the agent to read the matching qencode://recipe/... resource and submit via start_encode2_raw.
ABR / packaging: encode_hls_abr, encode_dash_abr, encode_mp4_ladder, encode_incremental_rung, encode_refreshing_playlist, remux_repack
Codecs / quality: encode_av1, encode_lcevc, tune_per_title, check_vmaf, ai_upscale_video, convert_hdr_to_sdr
Audio / images / text: extract_audio, generate_thumbnails, generate_smart_thumbnails, generate_waveform, transcribe, add_subtitles
Editing / framing: trim_clip, rotate_video, deinterlace_video, enable_smart_crop, add_watermark, add_html_overlay
Immersive: enable_vr_mode, inject_360_metadata
Analysis: get_video_metadata, analyze_video, detect_ai_generated
Probe / stitch: stitch_videos
Production hooks: enable_callbacks, enable_reliability
DRM: encode_aes128_hls, encode_widevine_ezdrm, encode_playready_ezdrm, encode_fairplay_ezdrm, encode_drm_buydrm, encode_drm_expressplay, encode_drm_doverunner, encode_forensic_watermark
transcode_video and start_encode2_raw accept source values with schemes https://, http://, s3://, or tus:. FTP/SFTP and private/metadata URLs are rejected at the tool boundary (SSRF defence). See docs/security/THREAT_MODEL.md for limitations.
Authentication is OAuth 2.1 only — there is no static-API-key mode. Your Qencode API keys never leave the portal; the server derives a fresh, short-lived session token per request via an internal portal endpoint. Source URLs are validated at the tool boundary (SSRF defence — see Source URL rules).
Full threat model and adversarial test coverage: docs/security/THREAT_MODEL.md.
uv venv && uv pip install -e ".[dev]"
NO_NETWORK=1 pytest -q # offline L1 + L2 + L5 (~900 tests) pytest -m protocol # MCP wire conformance only pytest -m unit # per-tool logic (FakeQencode) pytest -m security # OWASP MCP Top 10 adversarial suite
Protocol tests run fully offline (mocked Authorization Server, portal, and Qencode API). CI is the Jenkins job mcp_automated_tests (Jenkinsfile.manual): manual checkboxes for any layer, nightly L3 cron, weekly L4 cron.
Clients negotiate a version at initialize. This server targets [MCP 2025-11-25](https://modelcontextprotocol.io/specification/2025-11-25) as the primary version. CI also runs conformance tests against 2025-06-18 because JSON-RPC batching behavior differs between earlier revisions. We do not claim support for 2025-03-26 or older wire semantics beyond what the underlying SDK negotiates.
| Version | Support | Notes |
|---|---|---|
| 2025-11-25 | Primary | Streamable HTTP, resumable SSE where used |
| 2025-06-18 | CI matrix | Regression guard for mid-2025 clients |
| 2025-03-26 | Not targeted | Batching semantics differ from 2025-06-18 |
The connector users install is the hosted endpoint above. For Glama Servers / awesome-mcp-servers scoring only, this repo also ships qencode-mcp-inspect (stdio, dummy env, tools/call refused). That is not a supported client transport. See docs/glama-release.md.
docs/local-development.mddocs/testing.md and tests/README.md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