The open retrieval layer for AI agents. Index your entire project — code, docs, legal, research, data — and serve surgical context via MCP. FTS5 full-text search, optional semantic search (FastEmbed/ONNX), 10 built-in parsers, incremental auto-sync.
A local-first knowledge base for LLM coding agents that indexes repository documentation, concept ontology, and build targets into Qdrant and exposes retrieval as MCP tools (search, get, list sources, reindex).
Universal documentation knowledge-graph MCP server with hybrid full-text + vector search. Indexes local files and remote sources from Notion, Jira, Obsidian, Linear, GitHub, and Confluence into a single SQLite knowledge graph, exposing it to AI agents via the Model Context Protocol.
MCP-native knowledge base for AI agents — vault-scoped docs, tables, and files, git-versioned, with hybrid search (BM25 + pgvector dense + reranker) and an event stream so external consolidators / gardeners stay decoupled.
MCP server for a shared Postgres-backed knowledge base with hybrid retrieval and agentic RAG, enabling coding agents to upload, search, and ask questions over documents with cited answers.
Indexes documentation sites by base URL and serves keyword search, optional semantic search, and Markdown page retrieval as MCP tools, all from a single SQLite file.