Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
Video pipeline for AI agents: analyze with AI, transcode to MP4/HLS/DASH, edit, protect and deliver.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://mcp.qencode.com/mcp在终端中运行这条命令
claude mcp add --transport http qencode https://mcp.qencode.com/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"qencode": {
"url": "https://mcp.qencode.com/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"qencode": {
"type": "http",
"url": "https://mcp.qencode.com/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://mcp.qencode.com/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过域名 qencode.com 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.2.0)于16天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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只显示了开头部分;其余内容请在仓库中阅读