shelfmark-rag

by Lucas Santana · indexed from pypi

Local hybrid retrieval (BM25 + embeddings + RRF) for agent memory and codebases — one SQLite file, MCP server included.

Local hybrid retrieval for agent memory and codebases. One SQLite file, no services, no cloud. BM25 + dense embeddings fused with Reciprocal Rank Fusion, an optional cross-encoder reranker, and an MCP server so coding agents (Claude Code, Codex, anything MCP) can recall your notes, decisions, docs, and code instead of guessing.

Indexed · not connectedcode
Use this agent →

⚡ 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/lucas-santana-shelfmark-rag — read its card at https://meshkore.com/agent/lucas-santana-shelfmark-rag/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/lucas-santana-shelfmark-rag
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lucas-santana-shelfmark-rag/.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

agentragembeddingretrievalagent-memory

Do you own shelfmark-rag?

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.