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caura
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caura

Active·★ 506·Apache-2.0·Updated 2026-10-27
★ Trending

Caura is an open-source, shared, governed memory layer designed for multi-tenant, multi-agent AI fleets. It enables agents to store what they learn, find fleet knowledge, and improve through interaction, learning from each other and avoiding repeated mistakes.

caura sits in the Memory & Context category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Tenant isolation, visibility scopes, and agent trust tiers for robust governance.. A representative use case is Enable multi-tenant, multi-agent AI fleets to share learned knowledge and avoid repeating mistakes.. The listed license is Apache-2.0. GitHub stars are currently 504. Relevant tags include AI Agents, Fleet Memory.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool.

#AI Agents#Fleet Memory#Knowledge Graph#Vector Search#Multi-Agent Systems#Governance#LLM Integration#Memory Management
$ Install
$ git clone https://github.com/caura-ai/caura.git && cd caura-memclaw && cp .env.example .env && echo "IS_STANDALONE=true" >> .env && docker compose up -d
↗ Visit site★ GitHub
01

Features

01Tenant isolation, visibility scopes, and agent trust tiers for robust governance.
02Single-pass LLM enrichment and hybrid search with knowledge graph expansion.
03Outcome-based learning, crystallization, and per-agent retrieval tuning for self-improvement.
04MCP server, multi-provider LLM support, and a structured document store.
02

Why choose it

+Tenant isolation, visibility scopes, and agent trust tiers for robust governance.
+Single-pass LLM enrichment and hybrid search with knowledge graph expansion.
+Enable multi-tenant, multi-agent AI fleets to share learned knowledge and avoid repeating mistakes.
+Supports 5 platforms or runtime environments.
03

Trade-offs

!The final decision should still be made through side-by-side comparison with similar tools.
04

Compatibility

Docker
Deployment
Verified via docs
PostgreSQL
Database
Verified via docs
Python
Client SDK
Verified via docs
OpenAI
LLM Provider
Verified via docs
MCP Clients
Agent Framework
Verified via docs
05

Quick start

1
$ git clone https://github.com/caura-ai/caura.git
2
$ cd caura-memclaw
3
$ cp .env.example .env
4
$ echo "IS_STANDALONE=true" >> .env
5
$ docker compose up -d
06

Use cases

↳Enable multi-tenant, multi-agent AI fleets to share learned knowledge and avoid repeating mistakes.
↳Provide shared, governed memory for companies with dozens or thousands of AI agents.
↳Equip agents with long-term memory, context management, and auto-extracted knowledge graph capabilities.
↳Integrate with MCP clients like Claude Code, Cursor, or Windsurf for advanced memory functionality.
07

Alternatives

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07Alternatives
caura-ai /
caura
↗

Caura (formerly MemClaw) — governed shared memory for AI agent fleets. Multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.

506Apache-2.0
Last commit1d ago
StatusActive
CategoryMemory & Context
Links
Documentation↗Discussion↗Issues↗Releases↗
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