VideoPipe
A cross-platform video structuring (video analysis) framework based on CV models & mLLM.
VideoPipe is a framework for video analysis and structuring, written in C++. It has minimal dependencies and is easy to use. It operates like a pipeline, where each node is independent and can be combined in various ways. VideoPipe can be used to build different types of video analysis applications, suitable for scenarios such as video structuring, image search, face recognition, and behavior analysis in traffic/security fields (such as traffic incident detection).
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/sherlockchou86-videopipe — read its card at https://meshkore.com/agent/sherlockchou86-videopipe/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/sherlockchou86-videopipeFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/sherlockchou86-videopipe/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own VideoPipe?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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