AI Memory & Knowledge Base System for Claude Code
Initialize projects in seconds β’ Never lose context again
Claude OS is Claude Code's personal memory system - making AI the best coding assistant in the universe by remembering everything across sessions.
You work with Claude Code on a feature, close the terminal, come back tomorrow... and Claude forgot everything. You explain the same architecture. You reference the same files. You repeat yourself constantly.
Claude OS gives Claude persistent memory:
- π Remembers decisions across all sessions
- π Searches past work automatically at session start
- π Indexes your docs and makes them searchable
- π§ Learns patterns that improve over time
- π 100% Local - Never leaves your machine, fully private
β
Lightning-Fast Indexing - NEW! Tree-sitter hybrid indexing: 10,000 files in 30 seconds (vs 3-5 hours)
β
Real-Time Kanban Board - NEW! Auto-syncing task visualization for agent-os specs (updates within 3 seconds)
β
One-Command Project Init - /claude-os-init and you're done
β
Automatic Context Loading - Starts every session with relevant memories
β
Session Management - Track work, save progress, resume later
β
Documentation Ingestion - Auto-indexes your docs during setup
β
Agent-OS Integration - Optional spec-driven development with 8 specialized agents
β
Flexible AI - Choose local Ollama (free) or OpenAI API (paid)
β
Template System - Commands and skills shared via symlinks
Claude OS v2.0 introduces lightning-fast tree-sitter based indexing!
Previous versions embedded EVERY file, which was painfully slow for large codebases:
- Pistn project (10,000 Ruby files): 3-5 hours to index
- Must complete before Claude can start working
- High resource usage, blocks productive coding
Inspired by Aider's approach, Claude OS now uses:
Phase 1: Structural Index (30 seconds)
- β‘ Parse files with tree-sitter (no LLM calls!)
- π Extract symbols only (classes, functions, signatures)
- π Build dependency graph
- π PageRank importance scoring
- β Ready to code immediately!
Phase 2: Semantic Index (optional, background)
- π― Selective embedding (top 20% most important files)
- π Full embedding for documentation
- π Deep semantic search when needed
- β° Runs in background while you code
| Feature | Before | After (Hybrid) |
|---|---|---|
| Pistn (10k files) | 3-5 hours | 30 seconds + 20 min optional |
| Files embedded | 100,000+ chunks | ~20,000 chunks (80% reduction) |
| Start coding | After full index | Immediately! |
| Resource usage | High Ollama load | Minimal CPU/memory |
| Query speed | Semantic search | Instant structural + semantic |
π Read the full design: docs/HYBRID_INDEXING_DESIGN.md
Claude OS provides a beautiful, intuitive web interface for managing your AI development workflow:
π See the complete visual guide: docs/guides/VISUAL_GUIDE.md
Claude OS is built on 5 core pillars that work together to give Claude persistent memory:
- π§ Real-Time Learning - Automatically captures insights from conversations via Redis Pub/Sub
- πΎ Memory MCP - Persistent memory system with instant recall using natural language
- π Analyze-Project - Intelligent codebase indexing with git hooks and tree-sitter
- π― Session Management - Auto-resume sessions with full context preservation
- π Semantic Search - Vector-based code understanding and pattern recognition
All knowledge flows through the Semantic Knowledge Base (SQLite + sqlite-vec), exposed via the MCP Server (port 8051) to Claude Code, giving you an AI assistant that never forgets.
Data Flow: Git Commit β 3s indexing β SQLite β MCP β Claude β You
Note: The
install.shscript currently supports macOS only. Linux and Windows support coming soon.
Required:
- macOS (for
install.sh) - Python 3.11 or 3.12 (
python3 --version)- Note: Python 3.13+ not yet supported due to dependency constraints
- Git (
git --version)
Optional:
- Node.js 16+ (for React UI)
- Ollama (for local AI) or OpenAI API key
# Clone the repository
git clone https://github.com/brobertsaz/claude-os.git
cd claude-os
# Run the installer
./install.shThe installer will:
- β Set up Python virtual environment
- β Install all dependencies
- β Configure MCP server
- β
Symlink commands and skills to
~/.claude/ - β Create start script
If you want to use local AI with Ollama:
# 1. Clone the repository
git clone https://github.com/brobertsaz/claude-os.git
cd claude-os
# 2. Run the full setup script (installs Ollama + Redis)
./setup.sh
# 3. Start all services
./start_all_services.shThe setup script automatically installs:
- β Ollama (if not present) + LLM models
- β Redis (if not present) for caching/queues
- β Python virtual environment
- β All Python dependencies
- β SQLite database
- β Frontend dependencies (if Node.js present)
Visit http://localhost:5173 to use the web UI.
After installation, start the services:
./start.shThis starts the MCP server at http://localhost:8051
Initialize any project with Claude OS in under 2 minutes:
cd /path/to/your/projectIn Claude Code, run:
/claude-os-init
The command will:
-
Ask Questions Interactively:
- Project name (auto-detects from folder)
- Tech stack (Ruby on Rails, Python, Node.js, etc.)
- Database (PostgreSQL, MySQL, etc.)
- Development environment (Docker, Local, etc.)
- Brief description
- Documentation directory to ingest (optional)
-
Create Project in Claude OS:
- Calls API to create project
- Creates 4 knowledge bases automatically:
{project}-project_memories- Claude's memory{project}-project_profile- Architecture & standards{project}-project_index- Codebase index{project}-knowledge_docs- Your documentation
-
Set Up Project Structure:
your-project/ βββ CLAUDE.md # Auto-loaded every session! βββ .claude/ # Commands, skills, agents β βββ ARCHITECTURE.md β βββ CODING_STANDARDS.md β βββ DEVELOPMENT_PRACTICES.md βββ .claude-os/ # Config and state (git-ignored) βββ config.json βββ hooks.json -
Ingest Documentation:
- Scans your docs directory
- Uploads all files to
{project}-knowledge_docs - Creates vector embeddings for search
-
Analyze Codebase:
- Runs
initialize-projectskill - Generates coding standards
- Documents architecture
- Indexes key files
- Runs
-
Ready to Code:
- Claude now knows your project
- Memory persists across sessions
- Context auto-loads on session start
- β 4 knowledge bases created (memories, profile, index, docs)
- β Documentation auto-indexed
- β Codebase analyzed
- β CLAUDE.md file with all context
- β Ready to code with AI memory!
Every Claude Code session automatically:
-
Checks for Active Session
- Reads
claude-os-state.json - Prompts: Continue working? Start something new?
- Reads
-
Loads Context
- Searches
{project}-project_memoriesfor recent work - Loads relevant patterns and decisions
- Shows what it remembers
- Searches
-
Works With Memory
- Saves insights with
/claude-os-remember - Searches memories with
/claude-os-search - References past decisions automatically
- Saves insights with
-
Ends Session
- Saves session summary
- Updates memories
- Tracks what was accomplished
All these work in any initialized project:
/claude-os-init- Initialize new project/claude-os-search [query]- Search memories & docs/claude-os-remember [content]- Quick save to memories/claude-os-save [title]- Full-featured save with KB selection/claude-os-list- List all knowledge bases/claude-os-session [action]- Manage development sessions/claude-os-triggers- Manage trigger phrases
initialize-project- Analyze codebase and generate standardsremember-this- Auto-save when you say "remember this:"memory- Simple memory management
Created by Builder Methods (CasJam Media LLC) MIT Licensed β’ Separate Optional Integration
Agent-OS adds structured workflows for planning and implementing features using 8 specialized agents.
Agent-OS is a separate open-source project that can be installed alongside Claude OS. We're grateful to Builder Methods for creating such powerful spec-driven development tools.
If the Agent-OS repository is available, you can install it with:
git clone https://github.com/builder-methods/agent-os.git ~/.claude/agents/agent-osNote: Check if the repository exists before attempting to install.
If you have Agent-OS installed, use it when you want:
- Structured feature planning with iterative requirements gathering
- Detailed specifications before coding
- Task breakdowns with clear implementation steps
- Verification workflows to ensure completeness
Specification Workflow:
spec-initializer- Initialize new spec directoriesspec-shaper- Gather requirements through 1-3 questions at a timespec-writer- Create detailed technical specificationstasks-list-creator- Break specs into actionable tasks
Implementation Workflow:
implementer- Implement features following task listimplementation-verifier- Verify implementation completenessspec-verifier- Verify specs and tasks consistencyproduct-planner- Create product documentation
Available when enabled:
/new-spec- Initialize a new feature specification/create-spec- Full specification workflow (gather requirements β create spec β generate tasks)/plan-product- Create product mission, roadmap, and tech stack docs/implement-spec- Implement a specification following its tasks
1. User: "/new-spec user-authentication"
β Agent creates spec directory structure
2. User: "/create-spec"
β spec-shaper asks 1-3 questions at a time
β Gathers requirements iteratively
β Identifies reusable code
β Collects visual assets
3. Agent: spec-writer creates detailed specification
β tasks-list-creator generates actionable tasks
4. User: "/implement-spec user-authentication"
β implementer follows tasks step-by-step
β implementation-verifier checks completeness
5. Result: Fully specified, implemented, and verified feature!
When enabled, your project gets:
your-project/
βββ agent-os/
β βββ config.yml # Agent-OS configuration
β βββ product/ # Product documentation
β β βββ mission.md # Product mission
β β βββ roadmap.md # Feature roadmap
β β βββ tech-stack.md # Technology stack
β βββ specs/ # Feature specifications
β β βββ YYYY-MM-DD-feature-name/
β β βββ planning/
β β β βββ requirements.md
β β β βββ visuals/
β β βββ spec.md
β β βββ tasks.md
β βββ standards/ # Coding standards (as skills)
βββ .claude/agents/agent-os/ # 8 agents (symlinked)
Agent-OS agents deeply integrate with Claude OS:
- Search memories before creating specs (avoid reinventing)
- Save decisions to project_memories during planning
- Reference patterns from previous work
- Build knowledge that improves over time
This is the complete AI development system!
NEW: Real-time auto-syncing Kanban board for Agent-OS specs!
Visual Kanban board showing specs, tasks, and progress tracking
When you use Agent-OS to create specs with /create-spec, Claude OS automatically:
- π Parses tasks.md files - Extracts all tasks, phases, dependencies, and metadata
- ποΈ Stores in database - Tracks progress, completion, and time estimates
- π Displays as Kanban - Visual board showing specs and tasks by status
- β‘ Real-time sync - NEW! Auto-detects file changes and updates within 3 seconds
- π File watching - Monitors
agent-os/specs/folder for changes - β Auto-refresh - Board polls every 3 seconds for live updates
- ποΈ Archives completed specs - Keep your board focused on active work
Real-Time File Watching (NEW!):
- Automatically monitors your
agent-os/specs/folder - Detects changes to
tasks.mdandspec.mdfiles - 2-second debounce to batch rapid edits
- Auto-syncs to database within 3 seconds
- Frontend auto-refreshes every 3 seconds
- Total latency: ~6 seconds from file save to board update
Automatic Syncing:
- Syncs all specs from your project's
agent-os/specs/folder - Tracks task metadata (estimated time, dependencies, risk level)
- Auto-detects completed tasks (marked with β
or
[x]in tasks.md) - Supports both checkbox format and classic format
Progress Tracking:
- Status auto-updates based on completion:
planning- No tasks completed yetin_progress- Some tasks completedcompleted- All tasks done
- Progress percentage calculated automatically
- Time estimates tracked (estimated vs actual minutes)
Archive Feature:
- Archive completed specs to keep your board clean
- Archived specs hidden by default but can be viewed
- Preserves all task history for future reference
All spec tracking functionality is exposed via REST API:
# Get all specs for a project
GET /api/projects/{project_id}/specs
# Get all tasks for a spec
GET /api/specs/{spec_id}/tasks
# Update task status
PATCH /api/tasks/{task_id}/status
{
"status": "in_progress", # todo, in_progress, done, blocked
"actual_minutes": 15
}
# Sync specs from agent-os folder (manual)
POST /api/projects/{project_id}/specs/sync
# Get Kanban board view
GET /api/projects/{project_id}/kanban?include_archived=false
# Archive/unarchive specs
POST /api/specs/{spec_id}/archive
POST /api/specs/{spec_id}/unarchive
# NEW: Real-time spec watcher control
GET /api/spec-watcher/status
POST /api/spec-watcher/start/{project_id}
POST /api/spec-watcher/stop/{project_id}
POST /api/spec-watcher/start-allSee: docs/guides/REALTIME_KANBAN_GUIDE.md for complete documentation.
1. You create a spec with Agent-OS:
/create-spec β agent-os/specs/2025-01-15-user-auth/
2. Spec Watcher detects the new folder:
- Auto-starts when MCP server boots
- Monitors agent-os/specs/ directory
- 2-second debounce for batch changes
3. Auto-sync to database:
- Reads tasks.md
- Parses checkbox format: - [x] Task title
- Extracts metadata, tasks, phases
- Stores in SQLite database
- β
Completes within 3 seconds
4. View in Kanban board (auto-refreshes every 3 seconds):
- Todo: PHASE1-TASK1, PHASE1-TASK2
- In Progress: PHASE2-TASK1
- Done: PHASE1-TASK3, PHASE1-TASK4
5. As you work, agent-os updates tasks.md:
- File watcher detects change
- Auto-syncs to database
- Board refreshes automatically
- Total latency: ~6 seconds
6. Archive when complete:
- Mark spec as archived
- Keeps history but cleans up board
Two new tables track specs and tasks:
specs table:
- Stores spec metadata (name, path, status)
- Tracks total/completed tasks
- Calculates progress percentage
- Archive flag to hide completed specs
spec_tasks table:
- Individual tasks with codes (PHASE1-TASK1)
- Status (todo/in_progress/done/blocked)
- Time tracking (estimated vs actual)
- Dependencies between tasks
- Risk levels and phases
# Sync all Pistn specs
curl -X POST http://localhost:8051/api/projects/1/specs/sync
# Response:
{
"synced": 3,
"updated": 0,
"total": 3,
"errors": []
}
# Get Kanban view
curl http://localhost:8051/api/projects/1/kanban
# Response shows:
# - 3 specs with 52+ tasks
# - Tasks grouped by status
# - Progress percentages
# - Time estimatesThis is the complete AI development system!
claude-os/
βββ templates/ # Shared templates
β βββ commands/ # Slash commands (symlinked to ~/.claude/)
β β βββ claude-os-init.md
β β βββ claude-os-search.md
β β βββ ...
β βββ skills/ # Skills (symlinked to ~/.claude/)
β β βββ initialize-project/
β β βββ remember-this/
β β βββ memory/
β βββ project-files/ # Files created during /claude-os-init
β βββ CLAUDE.md.template
β βββ .claude-os/
β βββ config.json.template
β βββ hooks.json.template
βββ cli/ # CLI tools
β βββ claude-os-consolidate.sh
βββ install.sh # Quick setup script
βββ start.sh # Start services
Benefits:
- β Update once, all projects benefit
- β Symlinks mean instant updates
- β Consistent across projects
- Visit http://localhost:5173
- Create Knowledge Base:
- Click "Create Knowledge Base"
- Choose type (Generic, Code, Documentation, Agent_OS)
- Upload Documents:
- Select KB from dropdown
- Drag & drop files or click upload
- Supports .md, .txt, .pdf, .py, .js, .ts, .json, .yaml
- Query:
- Type question in search box
- View answer with source citations
# Search your project memories
/claude-os-search "how did we implement authentication?"
# Save a quick insight
/claude-os-remember "Fixed bug in user controller by adding validation"
# Full-featured save
/claude-os-save "Authentication Pattern" my-app-project_profile ArchitectureWhen you run /claude-os-init, you get 4 knowledge bases:
-
{project}-project_memories- Claude's memory for decisions, patterns, solutions
- Automatically saved during sessions
- Searched at session start
-
{project}-project_profile- Architecture, coding standards, practices
- Generated by
initialize-projectskill - Updated as project evolves
-
{project}-project_index- Automated codebase index
- Tracks file structure
- Updates on git commits (with hooks)
-
{project}-knowledge_docs- Your documentation
- Auto-ingested during init
- Add more via UI or CLI
# SQLite Database
SQLITE_DB_PATH=data/claude-os.db # Default: data/claude-os.db
# Ollama
OLLAMA_HOST=http://localhost:11434 # Default: localhost:11434
OLLAMA_MODEL=llama3.1:latest # Default: llama3.1:latest
# MCP Server
MCP_SERVER_HOST=0.0.0.0 # Default: 0.0.0.0
MCP_SERVER_PORT=8051 # Default: 8051Each project has .claude-os/config.json:
{
"project_name": "my-app",
"claude_os_url": "http://localhost:8051",
"knowledge_bases": {
"memories": "my-app-project_memories",
"profile": "my-app-project_profile",
"index": "my-app-project_index",
"docs": "my-app-knowledge_docs"
},
"docs_settings": {
"watch_paths": ["./docs", "./knowledge_docs"],
"auto_ingest_patterns": ["*.md", "*.txt", "*.pdf"]
},
"tech_stack": "Ruby on Rails",
"database": "MySQL"
}Native Ollama Setup:
- Response time: ~40 seconds per query
- GPU acceleration: Full Metal GPU on Apple Silicon
- Memory usage: 8-10GB (models + context)
- CPU usage: 12 cores (M4 Pro)
Why it's fast:
- Direct GPU acceleration (no virtualization)
- Efficient vector search in SQLite
- Optimized RAG engine with caching
- Single-file database with minimal overhead
./install.shAutomated setup script:
- β
Creates
~/.claude/directories - β Symlinks all commands and skills
- β Sets up Python environment
- β Installs dependencies
- β Configures MCP server
./setup.shComplete installation:
- β Installs Ollama + Redis (if needed)
- β Downloads LLM models (~5-10 GB)
- β Sets up Python environment
- β Creates database
./start.shStarts:
- π MCP Server (port 8051)
- π¨ React Frontend (port 5173)
- π€ RQ Workers
- πΎ Redis
- π§ Ollama
./stop_all_services.sh./restart_services.shSymlinks weren't created. Re-run:
cd /path/to/claude-os
./install.shClaude OS server isn't running:
cd /path/to/claude-os
./start.shProject name is taken. Choose a different name or delete via UI at http://localhost:5173
# Find process on port 8051
lsof -i :8051
# Kill if needed
kill -9 <PID># Check if running
ollama list
# Start manually
ollama serve
# Check for model
ollama list | grep llama3.1claude-os/
βββ templates/ # Shared templates system
β βββ commands/ # Slash commands
β βββ skills/ # Skills
β βββ project-files/ # Files created during init
βββ cli/ # CLI tools
β βββ claude-os-consolidate.sh
βββ app/ # Backend application
β βββ core/ # Core modules
β β βββ sqlite_manager.py
β β βββ rag_engine.py
β β βββ ...
β βββ db/ # Database schemas
βββ frontend/ # React UI (Vite)
β βββ src/
β βββ public/
β βββ assets/
β βββ claude-os-hero.png
βββ mcp_server/ # MCP Server (HTTP)
β βββ server.py # FastAPI + MCP endpoints
βββ data/ # SQLite database
β βββ claude-os.db
βββ logs/ # Service logs
βββ install.sh # Quick setup script
βββ start.sh # Start services
βββ README.md # This file
- templates/README.md - π Template system documentation
- docs/guides/REALTIME_KANBAN_GUIDE.md - β‘ NEW! Real-time Kanban board (auto-sync, file watching, API reference)
- docs/SELF_LEARNING_SYSTEM.md - π§ How Claude learns automatically
- docs/REAL_TIME_LEARNING_GUIDE.md - Real-time learning usage
- docs/MEMORY_MCP_GUIDE.md - Persistent memory guide
- docs/API_REFERENCE.md - π Complete API Reference (all endpoints, examples, authentication)
- docs/HYBRID_INDEXING_DESIGN.md - β‘ Hybrid indexing architecture
- README_NATIVE_SETUP.md - Detailed native setup
- NATIVE_VS_DOCKER_DECISION.md - Why native Ollama
- PERFORMANCE_TEST_RESULTS.md - Benchmark results
Claude OS is open source. Feel free to:
- Modify for your specific needs
- Add new commands and skills
- Optimize RAG strategies
- Contribute improvements back
Agent-OS Integration
Claude OS optionally integrates with Agent-OS by Builder Methods (CasJam Media LLC).
- Project: Agent-OS - Spec-driven development workflow system
- Author: Builder Methods (CasJam Media LLC)
- License: MIT
- Repository: https://github.com/builder-methods/agent-os
Agent-OS provides 8 specialized agents for structured feature planning and implementation. We're grateful to Builder Methods for creating such powerful tools and for licensing them under MIT, making this integration possible.
If you find Agent-OS valuable, consider:
- β Starring their repository
- π£ Sharing it with other developers
- π€ Contributing to their project
MIT License - Use it freely!
Note: This project (Claude OS) is MIT licensed. Agent-OS, when installed, is a separate project also MIT licensed by Builder Methods (CasJam Media LLC). See the Agent-OS repository for their specific license terms.
Claude Code + Claude OS = Invincible! π
Built by AI coders, for AI coders



