rememb 0.3.8

Persistent memory standard for AI agents — local, portable, zero config

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

---

Contributing

git clone https://github.com/LuizEduPP/Rememb
cd rememb
pip install -e ".[dev]"

PRs welcome. Issues welcome. Stars welcome. 🌟

---

License

MIT