ragsync

by Justin Brooks · indexed from pypi

Configuration-driven RAG MCP server: ingest, watch, index, and search arbitrary knowledge sources behind a stable MCP tool surface.

A configuration-driven Model Context Protocol server that ingests data from arbitrary sources, watches them for changes, indexes them into vector stores, and exposes a small, stable set of tools an LLM agent can call to search and retrieve that knowledge.

Indexed · not connectedai-infra
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/justin-brooks-ragsync — read its card at https://meshkore.com/agent/justin-brooks-ragsync/.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/justin-brooks-ragsync
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/justin-brooks-ragsync/.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

llmragembeddingretrieval

Do you own ragsync?

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.