System Architecture
Interactive visualization of ODAM for Cursor architecture
Features
🧠 Long-term Memory
Persistent memory across sessions, remembering project context and user preferences.
🔄 Automatic Sync
Automatically saves and retrieves context without manual intervention.
📝 Code Artifacts
Tracks code changes and artifacts to maintain project knowledge.
🔍 Context Injection
Injects relevant memory into chat context for better AI responses.
📊 Memory Analytics
View memory statistics and usage to understand system behavior.
Installation
From VSIX File
- 1.Download the latest .vsix file from Releases
- 2.Open Cursor
- 3.Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux)
- 4.Type: Extensions: Install from VSIX...
- 5.Select the downloaded .vsix file
From Source
git clone https://github.com/aipsyhelp/Cursor_ODAM.git
cd Cursor_ODAM/github-release
npm install
npm run compile
npm run packageThen install the generated .vsix file.
How It Works
ODAM integrates seamlessly with Cursor through official hooks and a local server
Cursor Hooks
Official beforeSubmitPrompt, afterAgentResponse, afterAgentThought hooks call cursor-odam-hook (auto-installed to ~/.cursor/hooks/odam-*.sh)
Hook Event Server
The extension runs a local secure HTTP server that accepts hook events in real time
Save Interactions
User queries and AI responses are saved to ODAM via /api/v1/code-memory/record
Retrieve Context
Relevant memory is retrieved via /api/v1/code-memory/context
Inject Context
Memory context is injected into .cursor/rules/odam-memory.mdc
Cursor Uses Context
Cursor automatically reads the memory file and uses it in chat
Benefits of ODAM's Approach
Semantic Understanding
Unlike keyword-based search, ODAM understands meaning and context
Long-Term Memory
Remembers project history, user preferences, and successful solutions
Error Prevention
Automatically avoids repeating past mistakes
Context Awareness
Provides relevant context based on semantic similarity, not just keywords
Scalability
Vector search scales to millions of memories efficiently
Privacy
User data is encrypted and isolated
Intelligence
Learns from past interactions to improve future responses
Memory Types
Episodic Memory
Specific conversations and events (timestamped)
Semantic Memory
Facts about the user and project (persistent)
Procedural Memory
Code patterns and solutions (reusable)
Emotional Memory
User preferences and style (personalized)
Data Security & Privacy
Encrypted Storage
All data is encrypted at rest (AES-256)
HTTPS Only
All API communication uses TLS 1.3
User Isolation
Data is strictly isolated per user (user_id) and project (session_id)
No Data Sharing
User data is never shared between users or projects
API Key Authentication
Secure API key-based authentication
Audit Logging
All data access is logged for security compliance