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sbolten/agy-memory-engine

Lightweight SQLite FTS5 dynamic memory layer & MCP server for Google Antigravity (AGY)

⭐ 4 stars
⑂ 0 forks
Python
momentum ▲ 8.0
created 2026-08-20
on radar since 2026-08-24
star trend 3 → 4 since 2026-08-24
View on GitHub ↗

About agy-memory-engine

Lightweight, high-performance, standalone dynamic memory layer for Google Antigravity (agy) and autonomous agent frameworks.

Inspired by Hermes Agent's 3-pillar memory architecture, using SQLite FTS5 for ultra-fast local retrieval ( Fuzzy Vectors for Core Facts: When an agent needs your timezone, server IPs, hardware specs, or personal preferences, SQLite FTS5 with BM25 ranking delivers deterministic, exact results in < 2ms with 0 MB extra RAM. - Telegram UX requires sub-second response starts: SQLite FTS5 pre-fetches relevant facts locally via standard library Python before the LLM begins streaming. - Zero External Dependencies: Built entirely on Python’s standard library (sqlite3, re, difflib). Runs anywhere without pip install, wheel compilation issues, or Docker container overhead. - Dynamic Pre-fetching without Prompt Bloat: Instead of dumping an entire personal wiki into the system prompt, agy-memory extracts key entities, fetches only the 3–5 relevant facts, and injects them as ephemeral context. - Autonomous Background Learning & Compaction: Ingesting new memories is decoupled from the user interaction (sync-turn). Over time, automated nightly compaction (compact --apply) deduplicates, resolves contradictions, and prunes stale data across all user accounts.

- ⚡ Blazing Fast Retrieval (<2ms): Uses native SQLite FTS5 full-text indexing with BM25 ranking. - 🔍 Typo & Fuzzy Fallback: Automatically handles misspelled terms and queries via difflib vocabulary matching. - 🌐 Multilingual & German/English Stopword Filtering: Filters out noise and matches keywords cross-lingu

From the project README.

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