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Search your Flashback video library with natural language to instantly find relevant moments. Get…
Search your Flashback video library with natural language to instantly find relevant moments. Get…
Remote endpoints: streamable-http: https://server.smithery.ai/@aryankeluskar/poke-video-mcp/mcp
Valid MCP server (1 strong, 3 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
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Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"ai-smithery-aryankeluskar-poke-video-mcp": {
"url": "https://server.smithery.ai/@aryankeluskar/poke-video-mcp/mcp"
}
}
}From the project's GitHub README.
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.
When connecting this MCP server to Poke or other MCP clients, you'll need to provide:
4087fce3-3d86-4047-b35f-4004b4c19192)Run the server:
uv run dev
Test interactively:
uv run playground
Query videos:
query_videos("person talking", max_results=5)
Get setup help:
get_setup_instructions()
Video Processing: Videos uploaded to Flashback are automatically:
Search Process: When you search:
Results: Each result includes:
query_videos(query: str, max_results: int = 10) -> strSearch for video clips based on natural language query.
Parameters:
query: Natural language description of what you're looking formax_results: Maximum number of results to return (1-15)Returns: Formatted text with video descriptions and URLs
get_setup_instructions() -> strGet detailed setup instructions for the video query system.
Returns: Complete setup and usage guide
api://video-processing: Information about the underlying video processing API# Search for specific content
query_videos("meeting discussion about deadlines")
query_videos("someone cooking in kitchen")
query_videos("red car driving")
# Limit results
query_videos("presentation", max_results=3)
Ready to deploy? Push your code to GitHub and deploy to Smithery:
Create a new repository at github.com/new
Initialize git and push to GitHub:
git add .
git commit -m "Video Query MCP Server 🎬"
git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git
git push -u origin main
Deploy your server to Smithery at smithery.ai/new
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