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FSRS-6 spaced repetition, spreading activation, synaptic tagging, hippocampal indexing, and 130 years of memory research. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> |
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Vestige
Git Blame for AI Thoughts - Memory that decays, strengthens, and discovers connections like the human mind.
Why Vestige?
| Feature | Vestige | Mem0 | Zep | Letta |
|---|---|---|---|---|
| FSRS-5 spaced repetition | Yes | No | No | No |
| Dual-strength memory | Yes | No | No | No |
| Sentiment-weighted retention | Yes | No | Yes | No |
| Local-first (no cloud) | Yes | No | No | No |
| Git context capture | Yes | No | No | No |
| Semantic connections | Yes | Limited | Yes | Yes |
| Free & open source | Yes | Freemium | Freemium | Yes |
Quickstart
# Install
npx vestige-mcp init
# Add to Claude Desktop config
# ~/.config/claude/claude_desktop_config.json (Mac/Linux)
# %APPDATA%\Claude\claude_desktop_config.json (Windows)
{
"mcpServers": {
"vestige": {
"command": "npx",
"args": ["vestige-mcp"]
}
}
}
# Restart Claude Desktop - done!
Key Concepts
Cognitive Science Foundation
Vestige implements proven memory science:
- FSRS-5: State-of-the-art spaced repetition algorithm (powers Anki's 100M+ users)
- Dual-Strength Memory: Separate storage and retrieval strength (Bjork & Bjork, 1992)
- Ebbinghaus Decay: Memories fade naturally without reinforcement using
R = e^(-t/S) - Sentiment Weighting: Emotional memories decay slower via AFINN-165 lexicon analysis
Developer Features
- Git-Blame for Thoughts: Every memory captures git branch, commit hash, and changed files
- REM Cycle: Background connection discovery between unrelated memories
- Shadow Self: Queue unsolved problems for future inspiration when new knowledge arrives
MCP Tools
| Tool | Description |
|---|---|
ingest |
Store knowledge with metadata (source, people, tags, git context) |
recall |
Search memories by query with relevance ranking |
get_knowledge |
Retrieve specific memory by ID |
get_related |
Find connected nodes via graph traversal |
mark_reviewed |
Reinforce a memory (triggers spaced repetition) |
remember_person |
Add/update person in your network |
get_person |
Retrieve person details and relationship health |
daily_brief |
Get summary of memory state and review queue |
health_check |
Check database health with recommendations |
backup |
Create timestamped database backup |
MCP Resources
| Resource | URI | Description |
|---|---|---|
| Recent memories | memory://knowledge/recent |
Last 20 stored memories |
| Decaying memories | memory://knowledge/decaying |
Memories below 50% retention |
| People network | memory://people/network |
Your relationship graph |
| System context | memory://context |
Active window, git branch, clipboard |
CLI Commands
# Memory
vestige stats # Quick overview
vestige recall "query" # Search memories
vestige review # Show due for review
# Ingestion
vestige eat <url|path> # Ingest documentation
# REM Cycle
vestige dream # Discover connections
vestige dream --dry-run # Preview only
# Shadow Self
vestige problem "desc" # Log unsolved problem
vestige problems # List open problems
vestige solve <id> "fix" # Mark solved
# Context
vestige context # Show current context
vestige watch # Start context daemon
# Maintenance
vestige backup # Create backup
vestige optimize # Vacuum and reindex
vestige decay # Apply memory decay
Configuration
Create ~/.vestige/config.json:
{
"fsrs": {
"desiredRetention": 0.9,
"maxStability": 365
},
"rem": {
"enabled": true,
"maxAnalyze": 50,
"minStrength": 0.3
},
"decay": {
"sentimentBoost": 2.0
}
}
Database Locations
| File | Path |
|---|---|
| Main database | ~/.vestige/vestige.db |
| Shadow Self | ~/.vestige/shadow.db |
| Backups | ~/.vestige/backups/ |
| Context | ~/.vestige/context.json |
How It Works
Memory Decay
Retention = e^(-days/stability)
New memory: S=1.0 -> 37% after 1 day
Reviewed once: S=2.5 -> 67% after 1 day
Reviewed 3x: S=15.6 -> 94% after 1 day
Emotional: S x 1.85 boost
REM Cycle Connections
The REM cycle discovers hidden relationships:
| Connection Type | Trigger | Strength |
|---|---|---|
entity_shared |
Same people mentioned | 0.5 + (count * 0.2) |
concept_overlap |
2+ shared concepts | 0.4 + (count * 0.15) |
keyword_similarity |
Jaccard > 15% | similarity * 2 |
temporal_proximity |
Same day + overlap | 0.3 |
Documentation
- API Reference - Full TypeScript API documentation
- Configuration - All config options
- Architecture - System design and data flow
- Cognitive Science - The research behind Vestige
Contributing
See CONTRIBUTING.md for guidelines.
License
MIT - see LICENSE
Vestige: The only AI memory system built on 130 years of cognitive science research.
