ShipItAndPray/mcp-memory

Smart memory for AI agents. Memories decay, topics are frequency-weighted, one-time questions don't become obsessions.
**Solves the Karpathy problem: "A single question from 2 months ago keeps coming up as a deep interest with undue mentions in perpetuity."**
What's New in v0.2.0
- **Auto-categorization** — no need to specify category, inferred from content
- **Semantic dedup** — bigram similarity prevents duplicate memories
- **Preference supersede** — "prefers dark mode" then "prefers light mode" updates, not duplicates
- **Recall auto-reinforces** — searching for a topic counts as a mention
- **Recall auto-prunes** — dead memories cleaned up on every read
- **System prompt injection** — active memories provided via MCP prompts capability
- **Fuzzy forget** — "VS Code" matches "User prefers VS Code for all editing"
- **7 tools → 4 tools** — simpler API, higher adoption (backwards compatible)
In Action
How It Fixes This
| Current LLM Memory | mcp-memory |
|---------------------|------------|
| Ask about Rust once → mentioned forever | Ask once → fades in 7 days |
| All memories equal weight | Categories: one-time (7d), question (14d), interest (60d), preference (180d) |
| No decay | Exponential decay — old memories naturally fade |
| No frequency tracking | Mentioned 5+ times → auto-upgrades from "question" to "interest" |
| Keyword matching | Bigram similarity + relevance scoring |
| Agent must decide to remember | Auto-categorizes from content patterns |
| Contradicting preferences coexist | New preference supersedes old one |
| Manual cleanup required | Auto-prunes dead memories on recall |
Install
Tools
| Tool | What it does |
|------|-------------|
| remember | Store a memory. Auto-categorizes from content. Auto-deduplicates via bigram similarity. Supersedes conflicting preferences. |
| recall | Retrieve memories ranked by relevance. Auto-reinforces top match. Auto-prunes dead memories. |
| forget | Delete a memory by ID or fuzzy content match. |
| inspect | Debug view: all memories with decay status, relevance scores, category breakdown, health. |
Auto-Categorization
No need to specify category — it's inferred from content:
| Content Pattern | Auto-Category | Decay |
|----------------|---------------|-------|
| "prefers X", "likes X", "always uses X" | preference | 180 days |
| "works as X", "is a X", "lives in X" | fact | 365 days |
| "actually X", "meant X", "wrong" | correction | 365 days |
| "currently building", "working on" | context | 30 days |