Releases: qualixar/superlocalmemory
v2.8.0 — Memory Lifecycle, Behavioral Learning, Enterprise Compliance
What's New
Memory Lifecycle Management — Memories automatically organize themselves over time based on usage patterns, keeping your system fast and relevant.
Behavioral Learning — The system learns from action outcomes and transfers knowledge across projects. Zero LLM inference — pure local pattern recognition.
Enterprise Compliance — Full access control, immutable audit trails, and retention policy management for GDPR, HIPAA, and EU AI Act.
6 New MCP Tools
| Tool | Purpose |
|---|---|
report_outcome |
Record action outcomes for behavioral learning |
get_lifecycle_status |
View memory lifecycle state distribution |
set_retention_policy |
Configure retention policies |
compact_memories |
Trigger lifecycle transitions |
get_behavioral_patterns |
View learned behavioral patterns |
audit_trail |
Query the compliance audit trail |
Upgrade
npm install -g superlocalmemory@latestDrop-in upgrade. All existing memories, settings, and configurations preserved. Upgrade Guide →
Full Changelog: CHANGELOG.md
Website: superlocalmemory.com
Research: superlocalmemory.com/research
SuperLocalMemory v2.7.4
What's New
Added
- Per-profile learning — each profile has its own preferences and feedback
- Thumbs up/down and pin feedback on memory cards
- Learning data management in Settings (backup + reset)
- "What We Learned" summary card in Learning tab
Improved
- Smarter learning from your natural usage patterns
- Recall results improve automatically over time
- Privacy notice for all learning features
- Learning and backup databases protected together
- All dashboard tabs refresh on profile switch
Full changelog: https://github.com/varun369/SuperLocalMemoryV2/blob/main/CHANGELOG.md
v2.7.0 — Your AI Learns You
SuperLocalMemory v2.7.0 — "Your AI Learns You"
Your memory system now learns your patterns, adapts to your workflow, and personalizes recall — all 100% locally on your machine.
Highlights
- Adaptive Learning — Three-layer learning: tech preferences, project context, workflow patterns
- Personalized Ranking — LightGBM LambdaRank re-ranking with 9 personalized features
- Privacy by Design — Separate
learning.dbfor behavioral data, GDPR Article 17 compliant, zero telemetry - Day-1 Intelligence — Synthetic bootstrap trains ML model from existing memories immediately
- Multi-Channel Feedback —
memory_usedMCP tool,slm usefulCLI, dashboard clicks - 12 MCP Tools — 3 new:
memory_used,get_learned_patterns,correct_pattern - 319 Tests — Unit, E2E, regression, fresh-install, and edge-case coverage
Install / Upgrade
# npm (recommended)
npm install -g superlocalmemory
# Or clone
git clone https://github.com/varun369/SuperLocalMemoryV2.git
cd SuperLocalMemoryV2 && bash install.shResearch Foundations
Built on peer-reviewed research: LambdaRank (Burges 2010), TSW-PrefixSpan (IEEE 2020), MACLA (arXiv:2512.18950), cold-start mitigation (LREC 2024), privacy-preserving feedback design.
Documentation
Created by Varun Pratap Bhardwaj — Solution Architect
v2.6.0 — Security Hardening & Performance
What's New
38 improvements across 6 phases, consolidating findings from 7 independent security audits. All changes are backward compatible — existing installations upgrade seamlessly.
Security
- Profile isolation on all query endpoints — memories from one profile can never leak to another
- Trust enforcement gate — agents with trust score below 0.3 are blocked from write operations
- Rate limiting on API and dashboard (100 writes/min, 300 reads/min per IP)
- SSRF protection for webhook URLs (private/internal IP blocking)
- SQL injection defense — table name whitelist validation in reset operations
- Error message sanitization — internal paths and table names stripped from all error responses
- Optional API key auth — opt-in authentication for write endpoints via
~/.claude-memory/api_key - Event content redaction — event payloads no longer leak memory content by default
Performance & Scalability
- Graph cap raised from 5,000 → 10,000 memories with intelligent sampling beyond the limit
- HNSW-accelerated graph building — O(n log n) edge construction instead of O(n²)
- HNSW-accelerated search — O(log n) memory lookups wired into the search pipeline
- Hybrid search engine — BM25 + Graph + TF-IDF fusion available via
SLM_HYBRID_SEARCH=true - TF-IDF incremental optimization — skip rebuilds when memory count changes less than 5%
- Read connection pool limit (50 connections) with graceful reuse
Reliability
- Database integrity check (
PRAGMA quick_check) on every startup - Incremental auto-vacuum for automatic space reclamation
- CORS restricted to known service ports (8765, 8417, 8766)
- Bounded write queue (1,000 entries) for backpressure protection
- Auto-prune for event table (every 100 events or 24 hours)
Infrastructure
- GitHub Actions CI — automated testing on Python 3.8, 3.10, 3.12
- Ghost agent cleanup — dashboard filters out disconnected agents
- SECURITY.md updated with encryption posture and defense-in-depth documentation
Documentation
- Graph scaling limits documented in README, wiki, and website
- All public docs harmonized for v2.6 features
- Wiki synced with 9 updated pages
Upgrade
cd ~/path/to/SuperLocalMemoryV2
git pull origin main
./install.shYour existing ~/.claude-memory/memory.db is fully compatible — no migration needed.
Full Changelog
v2.5.0 - Your AI Memory Has a Heartbeat
🎉 SuperLocalMemory v2.5.0 - "Your AI Memory Has a Heartbeat"
Major Feature Release | February 12, 2026 | Backward Compatible
SuperLocalMemory transforms from passive storage to active coordination layer. Every memory operation now triggers real-time events. Agents are tracked. Trust is scored. The dashboard is live.
🆕 What's New
Real-Time Event System
- Event Bus: Every memory write/update/delete fires real-time events via SSE, WebSocket, and Webhook
- Live Events Tab: Watch memory operations happen in real-time across all AI tools
- Event Subscriptions: Durable + ephemeral subscriptions with filters
Multi-Agent Coordination
- Agent Registry: Track which AI agents connect - protocol, trust score, write/recall counters
- Agents Tab: Dashboard view showing all connected agents with live statistics
- Provenance Tracking: Know who created each memory and via which protocol
Concurrency Fixed
- DbConnectionManager: SQLite WAL mode + write queue eliminates "database is locked" errors
- Thread-Safe: Multiple agents can write simultaneously without conflicts
- 5-second busy timeout: Patient retry instead of immediate failure
Trust Scoring (Silent Collection)
- Bayesian Trust Signals: Track agent behavior (cross-agent recalls, burst writes, quick deletes)
- Research-Grounded: Beta-Binomial posterior calculation
- Silent in v2.5: Scores collected but not enforced (enforcement in v2.6)
Complete Visual Documentation (85 Assets)
- 20 dashboard screenshots (real UI, light/dark modes)
- 7 CLI terminal mockups (professional styling)
- 5 animated GIFs (demos of key features)
- 3 video walkthroughs (installation, quick start, dashboard tour)
- 24 thumbnails (web-optimized previews)
- Updated wiki (74 image references, all placeholders removed)
- Enhanced website (carousel, feature galleries, visual guides)
📦 Installation
Quick Install (All Platforms)
```bash
npm install -g superlocalmemory
```
From Source
```bash
git clone https://github.com/varun369/SuperLocalMemoryV2.git
cd SuperLocalMemoryV2
./install.sh # Mac/Linux
or: .\install.ps1 # Windows
```
🔧 What Changed
Core Modules
- `memory_store_v2.py`: DbConnectionManager integration, event bus hooks, provenance tracking
- `mcp_server.py`: Singleton instance, agent registration, no more per-call overhead
- `ui_server.py`: Refactored to 9 modular route files (from 2008-line monolith)
- `ui/app.js`: Split into 13 modular files (from 1588-line monolith)
New Components
- `src/db_connection_manager.py` - Concurrency fix (WAL mode + write queue)
- `src/event_bus.py` - Real-time event broadcasting
- `src/subscription_manager.py` - Event subscriptions
- `src/webhook_dispatcher.py` - HTTP webhook delivery
- `src/agent_registry.py` - Agent tracking
- `src/provenance_tracker.py` - Memory origin tracking
- `src/trust_scorer.py` - Bayesian trust scoring
Database Schema
- 4 new tables: `memory_events`, `subscriptions`, `agent_registry`, `trust_signals`
- 4 new columns on memories: `created_by`, `source_protocol`, `trust_score`, `provenance_chain`
🐛 Fixes
- "Database is locked" errors: Eliminated via WAL mode + write serialization
- Fresh database crashes: Graceful empty responses when tables don't exist
- Per-call overhead: MCP handlers no longer rebuild vectorizer on every call
🧪 Testing
- 63 pytest tests: Unit, concurrency, regression, security, edge cases
- 27 end-to-end tests: All v2.5 components + 50 concurrent writes
- 15 fresh-database tests: New user scenarios
- 17 backward compatibility tests: Against live v2.4.2 database
- Playwright dashboard testing: All 8 tabs, SSE stream, profile switching
🌐 Website & Documentation
- Live Website: https://varun369.github.io/SuperLocalMemoryV2
- GitHub Wiki: https://github.com/varun369/SuperLocalMemoryV2/wiki
- Complete Visual Guide: 85 screenshots, GIFs, and videos
🔄 Upgrade Instructions
Automatic (Recommended)
```bash
npm update -g superlocalmemory
```
Manual
```bash
cd SuperLocalMemoryV2
git pull origin main
./install.sh # Mac/Linux
or: .\install.ps1 # Windows
```
Database Migration: Automatic. New tables and columns are created on first run.
🚀 What's Next
- v2.5.1 (April 2026): BMW Dashboard - Identity home, pattern viz, NL search
- v2.6 (May 2026): A2A Protocol - Agent-to-agent communication
- v2.7 (Jul-Aug 2026): Identity export/import + EU AI Act compliance
- v3.0 (Oct 2026): Enterprise multi-tenant platform
🙏 Credits
Created by: Varun Pratap Bhardwaj (Solution Architect)
License: MIT
Repository: https://github.com/varun369/SuperLocalMemoryV2
Research Foundations:
- Event Bus: Real-time memory systems
- Multi-Agent: A2A Protocol (Google/Linux Foundation)
- Trust Scoring: MACLA (arXiv:2512.18950)
- Knowledge Graph: GraphRAG (Microsoft, arXiv:2404.16130)
- Pattern Learning: MemoryBank (AAAI 2024)
Full Changelog: https://github.com/varun369/SuperLocalMemoryV2/blob/main/CHANGELOG.md
v2.3.7 - Critical Fix: Smart Content Truncation
v2.3.7 - Critical Fix: Smart Content Truncation
🐛 Critical Bug Fix
Problem: Recall was showing truncated content (200 chars max) even for short memories. Affected ALL IDEs using SuperLocalMemory.
Root Cause: Hardcoded [:200] truncation in memory_store_v2.py line 1014.
✨ What's Fixed
Smart Truncation
- Memories < 5000 chars: Show FULL content (no truncation) ✅
- Memories ≥ 5000 chars: Smart 2000 char preview with "..."
- 95%+ of memories now display in full by default
New Feature: --full Flag
Override truncation to always show complete content:
slm recall "query" --full
slm list --full
python3 ~/.claude-memory/memory_store_v2.py search "query" --fullBonus Fix
- Fixed
getcommand error (get_memory()→get_by_id())
🚀 How to Update
npm Users (Recommended)
npm update -g superlocalmemory
# or
npm install -g superlocalmemory@latestDirect Install Users
cd ~/SuperLocalMemoryV2
git pull origin main
bash install.shVerify Update
slm status
slm recall "test" # Should now show full content📦 Package Stats
- Version: 2.3.7
- Size: 403.1 KB compressed
- Files: 105
- Commit: da6972b
🔄 What Gets Updated
- ✅ Python backend (
memory_store_v2.py) - ✅ Node.js hooks (recall, list)
- ✅ All CLI commands
- ✅ MCP server compatibility
Your data is safe: Database and memories preserved.
🧪 Tested With
- ✅ 74+ existing memories
- ✅ Backward compatible (same output format)
- ✅ All IDEs: Claude, Cursor, Windsurf, VS Code, etc.
- ✅ All access methods: MCP, Skills, CLI
📚 Documentation
🙏 Credits
Issue reported by users across multiple IDEs. Fixed and tested with 74+ real-world memories.
npm: https://www.npmjs.com/package/superlocalmemory
GitHub: https://github.com/varun369/SuperLocalMemoryV2
v2.3.0 — Universal Integration
SuperLocalMemory V2.3.0 — Universal Integration Release
The architecture was always universal. Now the distribution is too.
What's New
- 4 new MCP configs: Codex CLI (TOML), VS Code/Copilot, Gemini CLI, JetBrains
slm servecommand: HTTP transport for ChatGPT and remote MCP clients- MCP tool annotations:
readOnlyHint,destructiveHint,openWorldHinton all 6 tools - Auto-detect 16+ tools: Codex, VS Code/Copilot, Gemini CLI, JetBrains added to
install.sh - Universal symlink:
~/.superlocalmemory→~/.claude-memoryfor non-Claude branding - Skills expansion: Cursor + VS Code/Copilot added to
install-skills.shwith--autoflag - npm is primary install:
npm install -g superlocalmemory
Supported Tools (16+)
| Tool | Integration |
|---|---|
| Claude Code | Skills + MCP |
| Cursor | MCP + Skills |
| Windsurf | MCP + Skills |
| Claude Desktop | MCP |
| OpenAI Codex | MCP + Skills |
| VS Code / Copilot | MCP + Skills |
| Continue.dev | MCP + Skills |
| Cody | Custom Commands |
| Gemini CLI | MCP + Skills |
| JetBrains IDEs | MCP |
| Zed Editor | MCP |
| OpenCode | MCP |
| Perplexity | MCP |
| Antigravity | MCP + Skills |
| ChatGPT | HTTP Transport |
| Aider | Smart Wrapper |
| Any Terminal | CLI |
Install
npm install -g superlocalmemoryOr manual:
git clone https://github.com/varun369/SuperLocalMemoryV2.git
cd SuperLocalMemoryV2 && ./install.shBackward Compatibility
100% backward compatible. Zero breaking changes. Existing data untouched.
Testing
- 68/68 regression tests passed
- Docker fresh install: passed (Python 3.11-slim)
- Docker backward compatibility: passed (existing data preserved)
100% local. 100% private. 100% universal.
Created by Varun Pratap Bhardwaj
SuperLocalMemory V2.1.0 - Universal Integration + Critical Fixes
SuperLocalMemory V2.1.0 - Universal Integration
Release Date: February 8, 2026
Status: Production Ready ✅
Testing: 100% pass rate on fresh Docker python:3.12 container
🚀 What's New
Universal Integration
- MCP Protocol: Auto-configures 11+ IDEs (Claude Desktop, Cursor, Windsurf, Continue.dev, Zed, OpenCode, Antigravity, Perplexity, ChatGPT Desktop, Cody, Aider)
- Universal Skills: 6 skills work across 5 AI tools (Claude Code, Continue.dev, Cody, Cursor, Windsurf)
- Single Database: All tools share one memory database (
~/.claude-memory/memory.db) - CLI:
slm remember,slm recall,slm statusavailable globally
Critical Bug Fixes (Feb 8, 2026)
Found via Docker testing on fresh systems (no pre-installed packages):
-
scikit-learn missing (
06236c1)- Added to
requirements-core.txt - Graph engine requires sklearn for TF-IDF vectorization
- Fresh installs failed without this dependency
- Added to
-
graph_engine.py column name mismatch (
82a1ca4)- Fixed:
name→cluster_name - Fixed:
member_count→memory_count get_stats()was querying non-existent columns
- Fixed:
-
pattern_learner.py column name mismatch (
7a9cf21)- Fixed:
key→pattern_key - Fixed:
value→pattern_value - Fixed:
evidence_count→frequency get_patterns()was querying non-existent columns
- Fixed:
📦 Installation
Quick Install (Mac/Linux)
# Download installer
curl -L -o SuperLocalMemory-v2.1.0-macos.dmg https://github.com/varun369/SuperLocalMemoryV2/releases/download/v2.1.0/SuperLocalMemory-v2.1.0-macos.dmg
# Mount and run installer
open SuperLocalMemory-v2.1.0-macos.dmgFrom Source
git clone https://github.com/varun369/SuperLocalMemoryV2.git
cd SuperLocalMemoryV2
./install.sh✅ Testing
Tested on:
- ✅ macOS (M1/M2)
- ✅ Docker python:3.12 (fresh container, no pre-installed packages)
- ✅ Ubuntu 22.04 LTS (simulated)
- ⏳ Windows 11 (manual testing recommended)
📖 Documentation
- Installation: https://github.com/varun369/SuperLocalMemoryV2/wiki/Installation
- Quick Start: https://github.com/varun369/SuperLocalMemoryV2/wiki/Quick-Start-Tutorial
- Architecture: https://github.com/varun369/SuperLocalMemoryV2/wiki/Universal-Architecture
- Changelog: https://github.com/varun369/SuperLocalMemoryV2/blob/main/CHANGELOG.md
🙏 Attribution
Created by Varun Pratap Bhardwaj
Solution Architect & Original Creator
Licensed under MIT License (attribution required)
Co-Authored-By: Claude Sonnet 4.5 noreply@anthropic.com
Website: https://varun369.github.io/SuperLocalMemoryV2
Free Domain: https://superlocalmemory.is-a.dev (pending approval)
SuperLocalMemory V2 - Initial Release
SuperLocalMemory V2 - Initial Release
A standalone intelligent memory system with knowledge graphs, pattern learning, and 4-layer architecture.
Features
- 4-Layer Architecture: Raw Storage → Hierarchical Index → Knowledge Graph → Pattern Learning
- 6 CLI Commands: remember, recall, list, status, reset, profile
- Knowledge Graph: Auto-discovers relationships using TF-IDF + Leiden clustering
- Pattern Learning: Learns your coding preferences with confidence scoring
- Progressive Compression: 60-96% space savings
- Multi-Profile Support: Isolated contexts for different projects
- Claude CLI Integration: Optional skills for
/superlocalmemoryv2:*commands - FastAPI UI Server: Visual exploration of your memory graph
Installation
git clone https://github.com/varun369/SuperLocalMemoryV2.git
cd SuperLocalMemoryV2
./install.shRequirements
- Python 3.8+
- SQLite3 (usually pre-installed)
Key Highlights
- 100% local - zero external APIs
- Complete privacy - your data stays on your machine
- Works standalone or with Claude CLI
- Built on research: GraphRAG, PageIndex, xMemory, A-RAG
Full documentation: README.md