Aryankeluskar Poke Video Mcp

ai.smithery由 smithery.ai 發布官方發布者v1.14.0更新於 Oct 24, 2026

Search your Flashback video library with natural language to instantly find relevant moments. Get…

發布方自己的服務:222wcnm Bilistalkermcp

已驗證Streamable HTTP可網頁執行網頁搜尋與抓取媒體與設計

概覽

AI 產生的概覽

一個遠端 MCP 伺服器,讓助理用自然語言搜尋你的 Flashback 影片庫,並回傳符合的片段及其描述與連結

可以做什麼
用自然語言查詢搜尋 Flashback 影片庫,取得依相關性排序的符合片段,附上 AI 產生的畫面描述與音訊轉錄,以及約 30 秒片段的直接連結、相關度分數和連結到期時間。取得影片查詢系統的設定與使用說明。以資源形式讀取底層影片處理 API 的資訊。
適用情境
適合已將影片上傳到 Flashback、希望助理透過描述畫面內容(例如演講、寵物奔跑或會議主題)來定位特定片段的場合,不必手動逐段翻看影片。
執行需求
透過 streamable HTTP 存取的遠端端點,需在 Authorization 標頭中提供用於 Smithery 身分驗證的 bearer 權杖。設定需要 Flashback 帳戶使用者 ID,並需能存取 Flashback 影片處理系統。影片須已上傳至該帳戶。
安裝前請注意
需要在 Authorization 標頭中提供 bearer 權杖和 Flashback 使用者 ID,兩者都應視為敏感資訊。查詢內容和帳戶識別碼會傳送到 Flashback 後端以及 Pinecone、Anthropic Claude、OpenAI Whisper、Google Cloud Storage 等第三方服務。影片連結為預先簽署連結,一小時後過期。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Aryankeluskar Poke Video Mcp,將其新增到工作區。
  2. 連接 Authorization token 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/ai.smithery%2Faryankeluskar-poke-video-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "aryankeluskar-poke-video": {
      "type": "http",
      "url": "https://server.smithery.ai/@aryankeluskar/poke-video-mcp/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

Video Query MCP Server

An MCP (Model Context Protocol) server that provides video search capabilities using natural language queries. This server interfaces with the Flashback video processing API to search through your personal video collection.

Features

  • 🔍 Natural Language Search: Query videos using everyday language (e.g., "person giving presentation", "dog running in park")
  • 🤖 AI-Generated Descriptions: Returns detailed descriptions of video content including visual analysis and audio transcription
  • 🎬 Video Clips: Get direct URLs to relevant 30-second video segments
  • ⚡ Fast & Secure: Presigned URLs with 1-hour expiration for secure access
  • 📊 Relevance Scoring: Results ranked by semantic similarity to your query

Setup

Prerequisites

  • Your Flashback account user ID
  • Access to the Flashback video processing system

Configuration

When connecting this MCP server to Poke or other MCP clients, you'll need to provide:

  • user_id: Your unique Flashback account identifier (e.g., 4087fce3-3d86-4047-b35f-4004b4c19192)

Development

  1. Run the server:

    bash
    uv run dev
  2. Test interactively:

    bash
    uv run playground

Usage Examples

Query videos:

query_videos("person talking", max_results=5)

Get setup help:

get_setup_instructions()

How It Works

  1. Video Processing: Videos uploaded to Flashback are automatically:

    • Split into ~30-second segments
    • Analyzed with AI for visual content
    • Transcribed for audio content
    • Stored in a searchable vector database
  2. Search Process: When you search:

    • Your query is converted to embeddings
    • The system finds matching video segments
    • Returns descriptions and URLs for relevant clips
  3. Results: Each result includes:

    • AI-generated description of the video content
    • Relevance score (0-1, higher = more relevant)
    • Direct URL to view the video segment
    • Expiration time for the URL

API Reference

Tools

query_videos(query: str, max_results: int = 10) -> str

Search for video clips based on natural language query.

Parameters:

  • query: Natural language description of what you're looking for
  • max_results: Maximum number of results to return (1-15)

Returns: Formatted text with video descriptions and URLs

get_setup_instructions() -> str

Get detailed setup instructions for the video query system.

Returns: Complete setup and usage guide

Resources

  • api://video-processing: Information about the underlying video processing API

Examples

python
# Search for specific contentquery_videos("meeting discussion about deadlines")query_videos("someone cooking in kitchen")query_videos("red car driving")
# Limit resultsquery_videos("presentation", max_results=3)

Troubleshooting

  • No results found: Check that videos have been uploaded to your Flashback account
  • "No description available": Older videos may need to be re-processed for full descriptions
  • Expired URLs: Video URLs expire after 1 hour for security - request fresh results if needed

Technical Details

  • Backend: FastAPI service deployed on Modal
  • Vector Database: Pinecone for semantic search
  • AI Models: Anthropic Claude for visual analysis, OpenAI Whisper for transcription
  • Storage: Google Cloud Storage for video files

Deploy

Ready to deploy? Push your code to GitHub and deploy to Smithery:

  1. Create a new repository at github.com/new

  2. Initialize git and push to GitHub:

    bash
    git add .git commit -m "Video Query MCP Server 🎬"git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.gitgit push -u origin main
  3. Deploy your server to Smithery at smithery.ai/new

來源:README.md,提交 2152b0d

工具

0
SourceWeft 尚未讀取此伺服器的工具。

版本歷史

1
  1. v1.14.0最新Sep 16, 2026

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