vestige
Cognitive memory system using FSRS-6 spaced repetition. Memories fade naturally like human memory. Use for persistent recall across sessions.
Install
mkdir -p .claude/skills/vestige && curl -L -o skill.zip "https://mcp.directory/api/skills/download/8760" && unzip -o skill.zip -d .claude/skills/vestige && rm skill.zipInstalls to .claude/skills/vestige
About this skill
Vestige Memory Skill
Cognitive memory system based on 130 years of memory research. FSRS-6 spaced repetition, spreading activation, synaptic tagging—all running 100% local.
Binary Location
~/bin/vestige-mcp
~/bin/vestige
~/bin/vestige-restore
When to Use
- Persistent memory across sessions
- User preferences ("I prefer TypeScript", "I always use dark mode")
- Bug fixes and solutions worth remembering
- Project patterns and architectural decisions
- Reminders and future triggers
Quick Commands
Search Memory
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"user preferences"}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
Save Memory (Smart Ingest)
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"smart_ingest","arguments":{"content":"User prefers Swiss Modern design style for presentations","tags":["preference","design"]}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
Simple Ingest
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"ingest","arguments":{"content":"TKPay Offline project: POC 2 months, MVP 2 months, budget 250K DH","tags":["project","tkpay"]}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
Check Stats
~/bin/vestige stats
Health Check
~/bin/vestige health
MCP Tools Available
| Tool | Description |
|---|---|
search | Unified search (keyword + semantic + hybrid) |
smart_ingest | Intelligent ingestion with duplicate detection |
ingest | Simple memory storage |
memory | Get, delete, or check memory state |
codebase | Remember patterns and architectural decisions |
intention | Set reminders and future triggers |
promote_memory | Mark memory as helpful (strengthens) |
demote_memory | Mark memory as wrong (weakens) |
Trigger Words
| User Says | Action |
|---|---|
| "Remember this" | smart_ingest immediately |
| "Don't forget" | smart_ingest with high priority |
| "I always..." / "I never..." | Save as preference |
| "I prefer..." / "I like..." | Save as preference |
| "This is important" | smart_ingest + promote_memory |
| "Remind me..." | Create intention |
Session Start Routine
At the start of conversations, search for relevant context:
# Search user preferences
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"user preferences instructions"}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text'
# Search project context
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"current project context"}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text'
Helper Script
For easier usage, create ~/bin/vmem:
#!/bin/bash
# Vestige Memory Helper
ACTION=$1
shift
case $ACTION in
search)
echo "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"search\",\"arguments\":{\"query\":\"$*\"}}}" | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
;;
save)
echo "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"smart_ingest\",\"arguments\":{\"content\":\"$*\"}}}" | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
;;
stats)
~/bin/vestige stats
;;
*)
echo "Usage: vmem [search|save|stats] [content]"
;;
esac
Data Location
- macOS:
~/Library/Application Support/com.vestige.core/ - Linux:
~/.local/share/vestige/ - Embedding cache:
~/Library/Caches/com.vestige.core/fastembed/
Integration Notes
Vestige complements the existing memory/ folder system:
- memory/*.md = Human-readable daily logs
- MEMORY.md = Curated long-term notes
- Vestige = Semantic search + automatic decay + spaced repetition
Use Vestige for:
- Things you want to recall semantically (not just keyword search)
- Preferences that should persist indefinitely
- Solutions worth remembering (with automatic decay if unused)
More by openclaw
View all skills by openclaw →You might also like
flutter-development
aj-geddes
Build beautiful cross-platform mobile apps with Flutter and Dart. Covers widgets, state management with Provider/BLoC, navigation, API integration, and material design.
drawio-diagrams-enhanced
jgtolentino
Create professional draw.io (diagrams.net) diagrams in XML format (.drawio files) with integrated PMP/PMBOK methodologies, extensive visual asset libraries, and industry-standard professional templates. Use this skill when users ask to create flowcharts, swimlane diagrams, cross-functional flowcharts, org charts, network diagrams, UML diagrams, BPMN, project management diagrams (WBS, Gantt, PERT, RACI), risk matrices, stakeholder maps, or any other visual diagram in draw.io format. This skill includes access to custom shape libraries for icons, clipart, and professional symbols.
ui-ux-pro-max
nextlevelbuilder
"UI/UX design intelligence. 50 styles, 21 palettes, 50 font pairings, 20 charts, 8 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient."
godot
bfollington
This skill should be used when working on Godot Engine projects. It provides specialized knowledge of Godot's file formats (.gd, .tscn, .tres), architecture patterns (component-based, signal-driven, resource-based), common pitfalls, validation tools, code templates, and CLI workflows. The `godot` command is available for running the game, validating scripts, importing resources, and exporting builds. Use this skill for tasks involving Godot game development, debugging scene/resource files, implementing game systems, or creating new Godot components.
nano-banana-pro
garg-aayush
Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an existing image file and asks to modify it in any way (e.g., "modify this image", "change the background", "replace X with Y"). Supports both text-to-image generation and image-to-image editing with configurable resolution (1K default, 2K, or 4K for high resolution). DO NOT read the image file first - use this skill directly with the --input-image parameter.
pdf-to-markdown
aliceisjustplaying
Convert entire PDF documents to clean, structured Markdown for full context loading. Use this skill when the user wants to extract ALL text from a PDF into context (not grep/search), when discussing or analyzing PDF content in full, when the user mentions "load the whole PDF", "bring the PDF into context", "read the entire PDF", or when partial extraction/grepping would miss important context. This is the preferred method for PDF text extraction over page-by-page or grep approaches.
Related MCP Servers
Browse all serversAgentKits Memory — local, persistent memory for AI coding assistants. On-premise SQLite with optional vector search for
AI Memory is a production-ready vector database server that manages and retrieves contextual knowledge with advanced sem
macOS Tools offers system monitoring and advanced file search with tagging on macOS, using SQLite for historical data an
Memory Bank: structured development workflow software with five modes to keep persistent project state and context acros
AGI MCP Server: persistent memory for AI with a vector database for AI, enabling episodic memory AI, semantic & procedur
Build persistent semantic networks for enterprise & engineering data management. Enable data persistence and memory acro
Stay ahead of the MCP ecosystem
Get weekly updates on new skills and servers.