palaia 2.4.dev1

Local, cloud-free memory for OpenClaw agents.

Palaia — The Knowledge System for AI Agent Teams

Crash-safe. Local-first. Zero-cloud. The memory system that makes your agents smarter over time.

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Install

Recommended: Tell your agent

Paste this into your OpenClaw agent (works for install AND update):

Install or update the Palaia memory skill from ClawHub to the latest version (even if already present). Read the SKILL.md completely and follow it step by step. Run palaia init, then palaia doctor --fix and resolve all warnings — don't stop until the doctor report is clean. Set up completely.

The agent handles everything: ClawHub skill install, pip setup, plugin config, and verification.

Manual Setup

pip install "palaia[fastembed]"
palaia init
palaia doctor --fix

Optional extras:

pip install "palaia[mcp]"          # MCP server for Claude Desktop, Cursor
pip install "palaia[curate]"       # Knowledge curation
pip install "palaia[postgres]"     # PostgreSQL + pgvector backend

Note: palaia[fastembed] already includes sqlite-vec for native vector search and the embed-server auto-starts on first query. No manual optimization needed.

Upgrading? palaia upgrade — auto-detects install method, preserves extras, runs doctor.

MCP Setup (Claude Desktop, Cursor, Claude Code — no OpenClaw needed)

pip install "palaia[mcp,fastembed]"
palaia init

Add to your MCP config:

• Claude Desktop: ~/.config/claude/claude_desktop_config.json
• Cursor: .cursor/mcp.json
• Claude Code: ~/.claude/settings.json

{
  "mcpServers": {
    "palaia": {
      "command": "palaia-mcp"
    }
  }
}

Quick Start

palaia write "API rate limit is 100 req/min" \
  --type memory --tags api,limits                   # Save knowledge
palaia query "what's the rate limit"                # Find it by meaning
palaia status                                        # Check health

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Why Palaia?

Feature	Details
Semantic Search	Hybrid BM25 + vector embeddings. 6 providers: fastembed, sentence-transformers, Ollama, OpenAI, Gemini, BM25.
Native Vector Search	sqlite-vec (SIMD KNN) or pgvector (ANN/HNSW). Not Python cosine — real database-level acceleration.
MCP Server	palaia-mcp — standalone memory for Claude Desktop, Cursor, any MCP host. No OpenClaw required.
Multi-Backend	SQLite (default, zero-config) or PostgreSQL + pgvector for distributed teams.
Crash-Safe	SQLite WAL mode — survives power loss, kills, OOM.
Auto-Capture	OpenClaw plugin captures significant exchanges automatically.
Structured Types	memory, process, task — with status, priority, assignee, due date.
Multi-Agent	Shared store, scopes (private/team/public), agent aliases, per-agent injection priorities.
Smart Tiering	HOT/WARM/COLD rotation based on decay scores and access patterns.
Embed Server	Background process holds model in RAM. CLI queries: ~1.5s (was ~3-5s). MCP/Plugin: <500ms.
Zero-Cloud	Everything local. No API keys needed for core functionality.

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Comparison

Feature	Palaia	claude-mem	Mem0	Stock Memory
Local-first	Yes	Yes	No (cloud)	Yes
Cross-tool (MCP)	Yes (any MCP client)	No (Claude Code only)	No	No
Native Vector Search	sqlite-vec / pgvector	ChromaDB (separate)	Cloud	No
Structured Types	memory/process/task	decisions/bugfixes	No	No
Multi-Agent Scopes	private/team/public	No	Per-user	No
Smart Tiering	HOT/WARM/COLD	No	No	No
Embedding Providers	6 (configurable)	1 (fixed)	Cloud	None
Open Source	MIT	AGPL-3.0	Partial	N/A
Crash-safe (WAL)	Yes	Partial	N/A	No

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Documentation

Document	Description
Getting Started	Installation, first steps, quick tour
Storage & Search	SQLite, PostgreSQL, sqlite-vec, pgvector, embedding providers
MCP Server	Setup for Claude Desktop, Cursor, tool reference, read-only mode
Embed Server	Performance optimization, socket transport, daemon mode
Multi-Agent	Scopes, agent identity, team setup, aliases
Configuration	All config keys, embedding chain, tuning
CLI Reference	All commands with flags and examples
Migration Guide	Import from other systems, flat-file migration
Architecture	Module map, data flows, design decisions
SKILL.md	Agent-facing documentation (what agents read)
Contributing	Versioning, release process, development setup
Changelog	Release history

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Development

git clone https://github.com/byte5ai/palaia.git
cd palaia
pip install -e ".[dev]"
pytest

Links

• palaia.ai — Homepage
• PyPI — Package registry
• ClawHub — Install via agent skill
• OpenClaw — The agent platform Palaia is built for
• CHANGELOG — Release history

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MIT — (c) 2026 byte5 GmbH