Vestige

Memory that fades like yours does.

The only MCP memory server built on cognitive science. FSRS-6 spaced repetition, spreading activation, synaptic tagging—all running 100% local.

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Why Vestige?

Problem	How Vestige Solves It
AI forgets everything between sessions	Persistent memory with intelligent retrieval
RAG dumps irrelevant context	Prediction Error Gating auto-decides CREATE/UPDATE/SUPERSEDE
Memory bloat eats your token budget	FSRS-6 decay naturally fades unused memories
No idea what AI "knows"	recall, semantic_search, hybrid_search let you query
Context pollution confuses the model	29 atomic tools > 1 overloaded tool with 15 parameters

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Quick Start

1. Install

git clone https://github.com/samvallad33/vestige
cd vestige
cargo build --release

Add to your PATH:

# macOS/Linux
sudo cp target/release/vestige-mcp /usr/local/bin/

# Or add to ~/.bashrc / ~/.zshrc
export PATH="$PATH:/path/to/vestige/target/release"

2. Configure Claude

Option A: One-liner (Recommended)

claude mcp add vestige vestige-mcp

Option B: Manual Config

Claude Code (~/.claude/settings.json)

{
  "mcpServers": {
    "vestige": {
      "command": "vestige-mcp"
    }
  }
}

Claude Desktop (macOS)

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "vestige": {
      "command": "vestige-mcp"
    }
  }
}

Claude Desktop (Windows)

Add to %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "vestige": {
      "command": "vestige-mcp"
    }
  }
}

3. Restart Claude

Restart Claude Code or Desktop. You should see 29 Vestige tools available.

4. Test It

Ask Claude:

"Remember that I prefer TypeScript over JavaScript"

Then in a new session:

"What are my coding preferences?"

It remembers.

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Important Notes

First-Run Network Requirement

Vestige downloads the Nomic Embed Text v1.5 model (~130MB) from Hugging Face on first use for semantic search.

All subsequent runs are fully offline.

Model cache location:

• macOS/Linux: ~/.cache/huggingface/
• Windows: %USERPROFILE%\.cache\huggingface\

Data Storage & Backup

All memories are stored in a single local SQLite file:

Platform	Database Location
macOS	~/Library/Application Support/com.vestige.core/vestige.db
Linux	~/.local/share/vestige/core/vestige.db
Windows	%APPDATA%\vestige\core\vestige.db

⚠️ There is no cloud sync, no redundancy, and no automatic backup.

If that file gets:

• Accidentally deleted
• Corrupted (disk failure, power loss mid-write)
• Lost (laptop stolen, hard drive dies)

...the memories are gone.

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For AI memory = Totally Fine

If you lose your Claude memories, you just start over. Annoying but not catastrophic.

For critical data = Not Fine

Don't store medical records, financial transactions, or legal documents in Vestige.

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Backup Options:

Manual (one-time):

# macOS
cp ~/Library/Application\ Support/com.vestige.core/vestige.db ~/vestige-backup.db

# Linux
cp ~/.local/share/vestige/core/vestige.db ~/vestige-backup.db

Automated (cron job):

# Add to crontab - backs up every hour
0 * * * * cp ~/Library/Application\ Support/com.vestige.core/vestige.db ~/.vestige-backups/vestige-$(date +\%Y\%m\%d-\%H\%M).db

Or just use Time Machine (macOS) / Windows Backup / rsync — they'll catch the file automatically.

For personal use with Claude? Don't overthink it. The memories aren't that precious.

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All 29 Tools

Core Memory

Tool	Description
ingest	Add new knowledge to memory
smart_ingest	Intelligent ingestion with Prediction Error Gating—auto-decides CREATE/UPDATE/SUPERSEDE
recall	Search by keywords, ranked by retention strength
semantic_search	Find conceptually related content via embeddings
hybrid_search	Combined keyword + semantic with RRF fusion
get_knowledge	Retrieve specific memory by ID
delete_knowledge	Remove a memory
mark_reviewed	FSRS review with rating (1=Again, 2=Hard, 3=Good, 4=Easy)

Feedback System

Tool	Description
promote_memory	Thumbs up—memory led to good outcome
demote_memory	Thumbs down—memory was wrong or unhelpful
request_feedback	Ask user if a memory was helpful

Stats & Maintenance

Tool	Description
get_stats	Memory system statistics
health_check	System health status
run_consolidation	Trigger decay cycle, generate embeddings

Codebase Memory

Tool	Description
remember_pattern	Save code patterns/conventions
remember_decision	Save architectural decisions with rationale
get_codebase_context	Retrieve patterns/decisions for current project

Prospective Memory (Intentions)

Tool	Description
set_intention	"Remind me to X when Y"
check_intentions	Check triggered intentions for current context
complete_intention	Mark intention as fulfilled
snooze_intention	Delay an intention
list_intentions	View all intentions

Neuroscience Layer

Tool	Description
get_memory_state	Check if memory is Active/Dormant/Silent/Unavailable
list_by_state	List memories grouped by cognitive state
state_stats	Distribution of memory states
trigger_importance	Retroactively strengthen recent memories (Synaptic Tagging)
find_tagged	Find high-retention memories
tagging_stats	Synaptic tagging statistics
match_context	Context-dependent retrieval (Encoding Specificity)

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How It Works

Prediction Error Gating

When you call smart_ingest, Vestige compares new content against existing memories:

Similarity	Action	Why
> 0.92	REINFORCE existing	Almost identical—just strengthen
> 0.75	UPDATE existing	Related—merge the information
< 0.75	CREATE new	Novel—add as new memory

This prevents duplicate memories and keeps your knowledge base clean.

FSRS-6 Spaced Repetition

Memories decay over time following the Ebbinghaus forgetting curve:

Retention = e^(-time/stability)

• Memories you access stay strong
• Memories you ignore fade naturally
• No manual cleanup required

FSRS-6 uses 21 parameters optimized on millions of Anki reviews—30% more efficient than SM-2.

Memory States

Based on accessibility, memories exist in four states:

State	Description
Active	High retention, immediately retrievable
Dormant	Medium retention, retrievable with effort
Silent	Low retention, rarely surfaces
Unavailable	Below threshold, effectively forgotten

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The Science

Vestige implements concepts from memory research:

Feature	Inspired By	Reference
Spaced repetition	FSRS-6 algorithm	Piotr Wozniak, 2022
Storage vs Retrieval strength	Bjork's New Theory of Disuse	Bjork & Bjork, 1992
Retroactive importance	Synaptic Tagging & Capture	Frey & Morris, 1997
Context-dependent retrieval	Encoding Specificity Principle	Tulving & Thomson, 1973
Forgetting curve	Ebbinghaus decay function	Ebbinghaus, 1885

Note

: These are simplified models inspired by cognitive science research, designed to be practical for AI memory management. They are not literal implementations of neural biochemistry.

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Configuration

Environment variables:

Variable	Default	Description
VESTIGE_DATA_DIR	Platform default	Custom database location
VESTIGE_LOG_LEVEL	info	Logging verbosity
RUST_LOG	-	Detailed tracing output

Command-line options:

vestige-mcp --data-dir /custom/path
vestige-mcp --help

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Troubleshooting

"Command not found" after installation

Make sure vestige-mcp is in your PATH:

which vestige-mcp
# Should output: /usr/local/bin/vestige-mcp

If not found:

# Use full path in Claude config
claude mcp add vestige /full/path/to/vestige-mcp

Model download fails

First run requires internet to download the embedding model. If behind a proxy:

export HTTPS_PROXY=your-proxy:port

"Tools not showing" in Claude

1. Check config file syntax (valid JSON)
2. Restart Claude completely (not just reload)
3. Check logs: tail -f ~/.claude/logs/mcp.log

Database locked errors

Vestige uses SQLite with WAL mode. If you see lock errors:

# Only one instance should run at a time
pkill vestige-mcp

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Development

# Run tests
cargo test --all-features

# Run with logging
RUST_LOG=debug cargo run --release

# Build optimized binary
cargo build --release --all-features

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Updating

cd vestige
git pull
cargo build --release
sudo cp target/release/vestige-mcp /usr/local/bin/

Then restart Claude.

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License

MIT OR Apache-2.0 (dual-licensed)

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Contributing

Issues and PRs welcome! See CONTRIBUTING.md.

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Built by @samvallad33