engram
Skill10 starsChanged 3 months agoMITView on GitHub
Persistent AI memory backend with semantic search and knowledge graph. Stores episodic, semantic, and procedural memories in a local SQLite database and retrieves the most relevant ones using vector similarity and graph traversal. Use when you need to remember information across sessions, recall past decisions, store facts about a project, detect contradictions between beliefs, or give any AI model a persistent growing brain. All embeddings run locally - no API keys required.
9 other projects use a version of this.
Adopted by
Most recently taken up by
- mazze93/claude-code-skillstheir own version, first seen Nov 1, 2026
- techtheist/engramtheir own version, first seen Oct 31, 2026
- JJHbrams/Project-AMBERtheir own version, first seen Oct 20, 2026
- eyeix/skillstheir own version, first seen Oct 13, 2026
- LucasXCoder/engramtheir own version, first seen Oct 9, 2026
- poorants/engramtheir own version, first seen Sep 30, 2026
Other versions9 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 9
- Patdolitse/piia-engram★ 165same name
- EngramMemory/engram-memory★ 36same name
- techtheist/engram★ 34same name
- DazhuangJammy/Engram★ 18same name
- JJHbrams/Project-AMBER★ 2same name
- eyeix/skills★ 1same name
- LucasXCoder/engram★ 1same name
- mazze93/claude-code-skills★ 1same name
- poorants/engram★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
Files
Engram AI Memory
Universal AI memory backend — give any AI model persistent, structured memory that survives sessions, systems, and restarts.
Tools (21 total)
| Category | Tools |
| Memory | store_memory, search_memory, recall_context, add_knowledge, forget |
| Stats | memory_stats, index_status, embedding_status |
| Lifecycle | decay_sweep, decay_policy, re_embed |
| Contradictions | check_contradictions, resolve_contradiction |
| Tags | list_tags, tag_memory |
| Webhooks | webhook_subscribe, webhook_list |
| Plugins | plugin_list |
| Reflection | request_reflection, store_reflection, get_reflections |
Recommended workflow
Session start → recall_context("current task or question")
During session → store_memory("decision or finding", type="episodic")
Session end → store_memory("session summary", importance=0.8)Key tools
recall_context— primary recall tool. Assembles the most relevant memories for a query and returns formatted context ready to inject into prompts. Call at the start of every session.store_memory— saves episodic events, semantic facts (type="semantic",concept="...") or procedural patterns (type="procedural").search_memory— semantic similarity search with optional type filter and threshold.check_contradictions— detects memories that conflict with a given memory ID.resolve_contradiction— resolves conflicts via strategy:keep_newest,keep_oldest,keep_important,keep_both, ormanual.decay_sweep— runs Ebbinghaus forgetting curve decay; archives stale memories and consolidates old episodes into facts.
Configuration
| Variable | Default | Description |
ENGRAM_DB_PATH | ~/.engram/engram.db | SQLite database path |
ENGRAM_NAMESPACE | (global) | Namespace filter — alone it only filters memories; set ENGRAM_NAMESPACE_MODE=isolated to isolate them |
ENGRAM_EMBEDDING_MODEL | Xenova/all-MiniLM-L6-v2 | Local ONNX embedding model |
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