Enables LLMs to search open-source AI models by semantic meaning using directional coordinates and anchors, returning scored, ranked results in under 100ms.
Provides 11 MCP tools for deterministic, local semantic search over your documents, including indexing, retrieval, exact-match facets, temporal truth, semantic diff, and agent-first JSON output. Enables LLMs and agents to search, retrieve, and analyze documents without cloud dependencies or per-query costs.
Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.
Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.