
Video URL Analyzer
io.github.u2n4由 GitHub 帳號 u2n4 發布v1.5.1更新於 Oct 24, 2026
Analyze YouTube/TikTok/Instagram videos: transcripts, AI insights, tutorial extraction
概覽
本機 MCP 伺服器,讓助理透過 Google Gemini 分析 YouTube、TikTok 與 Instagram 影片:逐字稿、問答、截圖、片段與教學步驟。
- 可以做什麼
- 以自訂提示分析影片或片段,並針對影片內容提問,依賴 Gemini 多模態理解,也支援 TikTok 與 Instagram 的圖文與輪播貼文。擷取含時間戳與講者標註的逐字稿,支援 100 多種語言。為每支影片儲存可重複使用的本機脈絡,之後依此回答追問,並可列出或刪除已儲存的脈絡、檢視快取中繼資料。擷取靜態畫面和短片段作為本機佐證素材,並可清理快取檔案,預設僅試跑。從技術類影片擷取教學步驟、shell 指令、程式碼片段與檔案路徑,供審閱,僅在確認後執行。輪詢 TikTok 與 Instagram 較長任務的非同步下載狀態。
- 適用情境
- 適合讓助理在不事先下載的情況下摘要、追問或挖掘某支 YouTube、TikTok 或 Instagram 影片,或把技術教學影片整理成可審閱的步驟。適用於研究、內容審閱與從影片學習,不適合大量爬取。
- 執行需求
- 透過 stdio 在本機執行,可用 uvx 或 pip 從 PyPI 安裝(需 Python 3.10+)。需要在 GEMINI_API_KEY 環境變數中提供 Google Gemini API 金鑰。截圖與片段擷取依賴 ffmpeg 與 yt-dlp,TikTok 與 Instagram 下載建議安裝 curl_cffi。需要連線至影片平台與 Google 的網路。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Video URL Analyzer,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Video Analyzer MCP Server
Analyze any video with AI — YouTube, TikTok & Instagram
Powered by Google Gemini 3.5 Flash · FastMCP · yt-dlp
[Gemini 3.5 Flash] [Python 3.10+] [MCP stdio] [Security Hardened] [MIT License]
Features · Architecture · Quick Start · Integration · Security · العربية
Features
[Features — Analyze, Transcript, Ask]
v1.5.4 exposes 18 MCP tools:
Supported Platforms
Photo / Slideshow Posts
YouTube videos are analyzed directly through Gemini's native video understanding — zero download, zero upload, maximum speed. For YouTube evidence assets,
source.mp4is not always required: saved contexts keep the original URL, so frame/clip tools can use the local stream fast path later.
Architecture
Operating Modes
These are behavior modes, not tool names:
Quick Start
The packaged runtime lives at src/video_url_analyzer_mcp/server.py; the
console entry point is video_url_analyzer_mcp:main. Pick whichever
install path matches your workflow.
Option A — one-line Windows installer (recommended for new users)
The installer follows the current MCP client pattern: it installs/runs from
PyPI with uvx, uses an existing GEMINI_API_KEY environment variable when
one is already set, otherwise asks for the key only through a hidden prompt,
and lets the user choose where to register the server:
- Claude Code
- Claude Desktop
- Codex CLI
- Cursor
- Windsurf
- VS Code / GitHub Copilot
- Google Antigravity
- Cline
Do not append your API key to the PowerShell command. If you skip the key,
the installer still registers the server and you can set GEMINI_API_KEY
later. If GEMINI_API_KEY is already set in your User environment, the
installer will use it directly and print only a masked form like
AIza...abcd.
Option B — uvx (no install)
Works on Windows / macOS / Linux as long as uv is on PATH.
Option C — Windows wizard from a checkout
The wizard:
- Verifies Python 3.10+ and (optionally)
uv. - Installs the package as an editable checkout or via
uv tool install. - Lets you save
GEMINI_API_KEYto a User environment variable or to a gitignored.env.keys.local. Keys are masked in logs (AIza...abcd), never printed in full. - Lets you pick a default model via
VIDEO_ANALYZER_MODEL. - Runs an offline import smoke test.
- Hands off to
scripts/configure_mcp_clients.ps1for client setup.
Option D — Manual install (any OS)
Get a free key at Google AI Studio,
then set it once in your shell environment (setx GEMINI_API_KEY ... on
Windows, or your ~/.zshrc / ~/.bashrc on macOS/Linux). For local dev
only, you can also drop it in a gitignored .env.keys.local next to the
repo.
Windows launcher
start.bat loads .env.keys.local (if present), sets safe defaults
(VIDEO_ANALYZER_MODE=auto), and runs python -m video_url_analyzer_mcp.
Use it as a command value in any MCP client that prefers a single
executable.
Integration
Run scripts/configure_mcp_clients.ps1 for an interactive menu, or copy
the snippets below from docs/mcp-config-examples.md. The wizard backs up
existing client config, validates JSON/TOML, and never overwrites unrelated
MCP servers.
Client configs use video-analyzer as the local MCP server entry name. The
published package remains video-url-analyzer-mcp, and the registry name
remains io.github.u2n4/video-url-analyzer-mcp.
Claude Desktop (%APPDATA%\Claude\claude_desktop_config.json)
The wizard prefers leaving the API key in your OS environment. If you must
embed it, add "env": { "GEMINI_API_KEY": "YOUR_KEY_HERE" }.
Claude Code (CLI)
Or, after pip install -e . in the repo:
Codex CLI (~/.codex/config.toml)
VS Code / GitHub Copilot MCP
Workspace registration writes .vscode/mcp.json:
For all clients, restart the application after editing config so the new
MCP server is picked up. Full snippets — including Cursor, Windsurf,
Antigravity (%USERPROFILE%\.gemini\antigravity\mcp_config.json), and
Cline — live in docs/mcp-config-examples.md.
Usage Examples
Security
This server has been hardened against a comprehensive threat model audit:
Environment Variables
Default fast model:
gemini-3.5-flash. Default deep model (used whendetail="full"):gemini-3.1-pro-preview. SetVIDEO_ANALYZER_MODELto override both at once. Model availability can vary by Google account, region, and API tier — fall back togemini-flash-latestif the latest ids are not yet enabled for your key. |VIDEO_ANALYZER_MODE| Behavior preset (auto/api/client/local); read bystart.bat|auto|
Troubleshooting
Tech Stack
License
MIT
العربية
خادم تحليل الفيديو بالذكاء الاصطناعي
خادم MCP لتحليل الفيديو باستخدام Google Gemini 3.5 Flash — احدث نموذج Gemini Flash متعدد الوسائط من جوجل.
المميزات
المنصات المدعومة
التثبيت السريع (ويندوز)
استنسخ الريبو ثم شغل المعالج التفاعلي:
البديل بدون تثبيت: uvx video-url-analyzer-mcp.
الامان
الخادم محمي ضد:
- SSRF — قائمة بيضاء للنطاقات المسموحة فقط
- حقن الاوامر — حظر الاوامر الخطيرة + تنفيذ بدون shell
- اختراق المسارات — حظر 25+ مسار حساس
- حماية من الحمل الزائد — حد اقصى 10 مهام متزامنة
الحصول على مفتاح API
- اذهب الى Google AI Studio
- انشئ مفتاح API مجاني
- ضعه في ملف
.env:
來源:README.md,提交 c33d3f6
工具
0版本歷史
1- v1.5.1最新Sep 16, 2026
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