memex

A local-first temporal knowledge graph memory layer for AI agents. Single Go binary, zero dependencies beyond SQLite. Runs entirely on your machine with Ollama — no API keys required.

Inspired by Vannevar Bush's 1945 vision of a personal knowledge machine, Memex gives AI agents persistent, searchable, graph-structured memory with temporal awareness.

• Local-first and private - Runs as a single Go binary with embedded SQLite, works out of the box with Ollama, and keeps data on your machine.
• Flexible model providers - Supports Ollama (local), OpenAI, Gemini, Vertex AI, Azure, and Groq, with per-knowledge-base model and credential isolation.
• Low-cost ingestion pipeline - Uses zero-LLM rule-based extraction for structured signals (errors, commits, config changes), with LLM fallback for rich text.
• Automatic memory capture - Learns passively via editor hooks (PostToolUse, PreCompact, UserPromptSubmit) and records feedback/corrections for closed-loop improvement.
• Temporal knowledge graph core - Builds entities, relations, and episodes with 3-tier entity resolution, bitemporal modeling, and relation strengthening instead of duplicate edges.
• Advanced graph retrieval - Full N-hop subgraph extraction, Personalized PageRank scoring, weight-aware traversal, edge-type filtering, community-seeded expansion, temporal path queries, and graph-to-text summarization for richer LLM context.
• Hybrid retrieval and lifecycle - Combines BM25 + vector + graph traversal with RRF, plus decay, pruning, and consolidation to keep memory relevant over time.
• Multiple interfaces - Includes a full MCP server (25 tools), HTTP API (20+ endpoints), and a 3-pane Bubble Tea TUI with graph explorer.
• Operationally ready - Provides async ingestion jobs with retries and one-command editor integration vi