Rememb
AI agents forget everything between sessions. rememb gives them persistent memory — local, portable, and works with any agent.
The problem
Every dev using AI professionally hits this wall:
Session 1: "We're using PostgreSQL, auth at src/auth/, prefer async patterns."
Session 2: Agent starts from zero. You explain everything again.
Session 3: Same thing.
Existing solutions (Mem0, Zep, Letta) require servers, API keys, and cloud accounts.
You just want the agent to remember your project.
Install
pip install rememb[mcp] # Recommended — includes MCP server
pip install rememb # CLI only
pip install rememb[mcp,semantic,pdf] # All features
Quick Start
With MCP (recommended)
Zero friction. No CLI commands. Native IDE integration.
1. Add to your IDE's MCP config:
{
"mcpServers": {
"rememb": {
"command": "rememb",
"args": ["mcp"]
}
}
}
2. Restart your IDE.
The agent now automatically reads memory at session start, writes when learning something new, and searches when needed.
Without MCP
rememb rules # Print generic rules for AI agents
Copy the output to your editor's rules file (.windsurfrules, .cursorrules, CLAUDE.md, etc.)
How it works
.rememb/
entries.json ← structured memory (project, actions, systems, user, context)
meta.json ← project metadata
A JSON file in your project. Your agent reads it at the start of every session.
User: "We're using PostgreSQL, auth at src/auth/, async patterns"
Agent: [rememb_write] → Saved
[New session]
Agent: [rememb_read] → Context loaded
Agent: "I see you're using PostgreSQL with auth at src/auth/..."
Search uses local semantic embeddings (no API, no cloud). Falls back to keyword search if embeddings aren't available.
Memory sections
| Section | What to store |
|---|---|
project | Tech stack, architecture, goals |
actions | What was done, decisions made |
systems | Services, modules, integrations |
requests | User preferences, recurring asks |
user | Name, style, expertise, preferences |
context | Anything else relevant |
CLI
rememb init # Initialize memory store
rememb write "text" # Add entry (--section, --tags)
rememb read # List all entries (--section, --agent)
rememb search "query" # Semantic/keyword search (--top)
rememb edit <id> # Update entry (--content, --section, --tags)
rememb delete <id> # Remove entry
rememb clear --yes # Delete all entries
rememb import <folder> # Import .md/.txt/.pdf files
rememb rules # Show generic rules for AI agents
Design
- Local first — plain JSON file in your project
- Portable — copy
.rememb/anywhere, it works - Agnostic — any agent, any IDE (MCP or CLI)
- No lock-in — no servers, no API keys, no accounts
Server Config
{
"mcpServers": {
"rememb": {
"command": "rememb",
"args": [
"mcp"
]
}
}
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