ragswift
🚀 Scale your RAG pipeline using Ragswift: A scalable centralized embeddings management platform
Ragswift, a scalable centralized embeddings platform, built to effortlessly handle document ingestion, storage and retrieval tasks at scale. Accelerate the development of RAG applications with ease. It eliminates the concerns associated with embeddings management within your RAG pipeline, you can just self host the solution and manage embeddings across multiple apps from a single place. It harnesses the power of distributed computing through Ray, empowering users to effortlessly process vast document sets in parallel across multiple CPU and GPU nodes.
⚡ 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/shivamsanju-ragswift — read its card at https://meshkore.com/agent/shivamsanju-ragswift/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/shivamsanju-ragswiftFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/shivamsanju-ragswift/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own ragswift?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.