Chariton-kyp Memgentic — Universal AI Memory Layer
Memgentic captures knowledge from all your AI tools and makes it searchable. Every memory carries full provenance: which tool, which session, when it happened.
When to Use
Search memory before doing work, not after:
- Starting a new task — Check for prior decisions, context, or related work.
- Making architectural decisions — Check if this was discussed before.
- Debugging — Search for related past issues and solutions.
- User asks about history — "what did we decide about...", "remember when...", "how did we handle..."
- Encountering unfamiliar code — Check for context on why it was written that way.
- Setting up or configuring something — Check for user preferences and conventions.
When in doubt, search. It costs little and prevents repeated work.
CLI Commands
Semantic Search (primary)
# Search memories by meaning
memgentic search "database migration strategy"
# Compact output — fewer tokens, good for scanning
memgentic search "database migration strategy" --format compact
# Filter by platform
memgentic search "auth implementation" -s claude_code
memgentic search "API design" -s chatgpt
# Filter by content type
memgentic search "why we chose PostgreSQL" -t decision
memgentic search "user coding style" -t preference
Store a Memory
# Save an important fact or decision
memgentic remember "We chose Qdrant over Pinecone for local-first vector storage"
# Memory type is auto-classified from content
memgentic remember "Always use UV for package management"
Other Commands
# See which platforms have memories and how many
memgentic sources
# Generate standalone context file with recent activity
memgentic update-context
# Explore knowledge graph around an entity
memgentic graph "authentication"
# Check system health
memgentic doctor
MCP Tools
If the Memgentic MCP server is running, these tools are available directly:
| Tool | Purpose |
|---|---|
memgentic_recall |
Semantic search with source filtering |
memgentic_remember |
Store a new memory |
memgentic_search |
Full-text keyword search |
memgentic_recent |
Recent memories by timestamp |
memgentic_briefing |
Cross-agent briefing of recent activity |
memgentic_sources |
List platforms and memory counts |
memgentic_configure_session |
Set session-level source filters |
memgentic_stats |
Memory statistics and analytics |
memgentic_forget |
Archive (soft-delete) a memory |
memgentic_export |
Export memories as JSON |
MCP Examples
memgentic_recall(query="authentication flow", limit=5)
memgentic_recall(query="auth", sources=["claude_code", "chatgpt"])
memgentic_remember(content="Project uses JWT with refresh tokens", memory_type="decision")
memgentic_search(query="PostgreSQL", content_type="decision")
memgentic_configure_session(exclude_sources=["codex_cli"])
memgentic_briefing(hours=24)
Efficient Retrieval Strategy
Minimize token usage with a progressive approach:
- Start compact — Use
--format compactfor an overview of what exists. - Narrow down — Add platform filter (
-s claude_code) or type filter (-t decision) when you know what you are looking for. - Full detail — Drop
--format compactonly when you need the complete memory content. - Limit results — Use
--limitto cap the number of results returned.
# Step 1: Quick scan
memgentic search "deployment" --format compact --limit 10
# Step 2: Found relevant results, get details from a specific platform
memgentic search "deployment" -s claude_code --limit 3
Memory Types
Memories are classified into types for filtering:
| Type | Contains |
|---|---|
decision |
Architectural and technical decisions with rationale |
learning |
Things learned during development |
preference |
User preferences, conventions, coding style |
fact |
General knowledge and project context |
bug_fix |
Bug fixes, root causes, and solutions |
conversation_summary |
Summaries of complete sessions |
Filter by type to get precise results:
memgentic search "database" -t decision # Only decisions about databases
memgentic search "testing" -t preference # Only testing preferences
memgentic search "auth" -t bug_fix # Only auth-related bug fixes
Cross-Platform Context
Memgentic captures from multiple AI tools. Each memory records its source platform:
| Platform | Source ID |
|---|---|
| Claude Code | claude_code |
| Gemini CLI | gemini_cli |
| ChatGPT | chatgpt |
| Aider | aider |
| Codex CLI | codex_cli |
| Copilot CLI | copilot_cli |
| Claude Web/Desktop | claude_web |
| Antigravity | antigravity |
Use source filtering to scope searches:
# What did we discuss in Claude Code about this project?
memgentic search "project architecture" -s claude_code
# What did ChatGPT suggest about this topic?
memgentic search "caching strategy" -s chatgpt
# See all available sources
memgentic sources
Capture Methods
Memories enter the system through:
- auto_daemon — File watcher captures conversations automatically in the background.
- mcp_tool — Stored via MCP tool calls during AI sessions.
- cli — Manually saved via
memgentic remember. - json_import — Bulk imported from conversation exports (ChatGPT, Claude Web).
Setup
# Check prerequisites
memgentic doctor
# Interactive setup (model selection, configuration)
memgentic setup
# Import existing conversations from all detected AI tools
memgentic import-existing
# Start background capture daemon
memgentic daemon
# Start MCP server for AI tool integration
memgentic serve