Khamel83/argus

Argus

Retrieval platform for AI agents. Argus routes search across 14 providers, recovers dead URLs, captures important site content, builds local docs-plus-research packs, and persists everything with traceable local artifacts.

Features at a glance:

• Topology-aware acquisition — Argus knows if it's on a residential IP or datacenter, routing search and extraction automatically to avoid blocks and minimize network hops.
• 14 providers, one API — free-first tier routing, budget-exhausted providers skipped automatically
• Zero-key start — pip install argus-search gives you DuckDuckGo + Yahoo immediately, no accounts needed
• SearXNG self-host = 70+ engines — Google, Bing, Yahoo, Startpage, Ecosia, Qwant and more via one Docker container
• 12-step content extraction — returns full page text with quality gates, not just links
• Opinionated retrieval workflows — recover dead articles, capture important pages from a site, and build local docs-plus-research packs
• Argus-owned corpus storage — runtime data goes to a writable user data directory, not your repo checkout
• Multi-turn sessions — pass session_id for conversational context across searches
• Score attribution — optionally show which providers contributed to each fused RRF score
• Usage dashboard — inspect provider budgets, recent query volume, and machine-level usage at /dashboard
• 4 search modes — discovery, research, recovery, grounding
• Dead URL recovery — /recover-url with Wayback Machine and archive fallbacks
• 4 integration paths — HTTP API, CLI, MCP server, Python SDK