Write a memory — no API key needed

<h1 align="center">Caura &mdash; Shared governed memory for AI agents</h1>

<h3 align="center">Fleet memory for AI agents &mdash; governed, shared, self-improving.</h3>

<p align="center"><strong>MemClaw is now Caura</strong> &mdash; same product, one name.<br /> <!-- legacy-name-floor: taught as legacy alias -->
Existing <code>memclaw_*</code> tool calls and supported <code>MEMCLAW_*</code> environment aliases continue to work; use <code>caura_*</code> names and current Caura URLs for new configuration. The PyPI name <code>memclaw-client</code> is kept only as a redirect shell (0.5.1) that installs <code>caura-client</code>; it provides no <code>memclaw_client</code> import and no <code>MemClaw</code> class. The npm package <code>@caura/memclaw-client</code> was never published.</p> <!-- legacy-name-floor: migration guidance and package evidence -->

<p align="center">
  <a href="LICENSE"><img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" alt="License" /></a>
  <a href="https://github.com/caura-ai/caura/stargazers"><img src="https://img.shields.io/github/stars/caura-ai/caura?style=social" alt="GitHub Stars" /></a>
  <a href="https://github.com/caura-ai/caura/actions"><img src="https://img.shields.io/github/actions/workflow/status/caura-ai/caura/ci.yml?label=CI" alt="CI" /></a>
  <a href="https://github.com/caura-ai/caura/releases"><img src="https://img.shields.io/github/v/release/caura-ai/caura" alt="Release" /></a>
  <a href="https://discord.com/invite/aNfpgfpj"><img src="https://img.shields.io/badge/Discord-join-5865F2?logo=discord&logoColor=white" alt="Join us on Discord" /></a>
</p>

<p align="center">
  <a href="#quick-start">Quick Start</a> &middot;
  <a href="#features">Features</a> &middot;
  <a href="#performance">Performance</a> &middot;
  <a href="#mcp-model-context-protocol">MCP</a> &middot;
  <a href="#api-reference">API Reference</a> &middot;
  <a href="static/docs/integration-guide.md">Plugin Docs</a> &middot;
  <a href="CONTRIBUTING.md">Contributing</a> &middot;
  <a href="https://discord.com/invite/aNfpgfpj">Discord</a>
</p>

---

## Caura (formerly MemClaw) — the shared governed memory layer for AI agent fleets <!-- legacy-name-floor: taught as legacy alias -->

Caura — formerly MemClaw — is open-source memory for **multi-tenant, multi-agent** AI fleets. Your agents store what they learn, find what the fleet knows, and get smarter with every interaction — learning from each other instead of repeating mistakes. <!-- legacy-name-floor: taught as legacy alias -->

Agents write plain text. Caura turns it into searchable, governed, self-improving memory.

**One loop, three pillars: write, recall, compound** — every interaction makes the next one smarter.

**Optimized for fleets.** One agent works, and that's where most teams start — nothing below changes for a single-agent setup. What Caura adds is headroom: scoped memory, cross-agent outcome propagation, and fleet-wide trust tiers are there from the first write, and they keep paying off as agents multiply. Public agent-memory benchmarks (LoCoMo, LongMemEval) measure one agent, one user, one long conversation — the single-chatbot shape — so they score the on-ramp rather than the axes that compound with agent count: latency, token efficiency, and governance. That second shape is what we see in production: dozens or thousands of agents working on behalf of one company, sharing what they learn under governance. See [Performance](#performance) for the numbers, or read the [benchmarks write-up](https://caura.ai/blog/caura-benchmarks).

> **In production at eToro (NASDAQ: ETOR):** 300+ AI agents on one governed
> memory — 26,500+ memories, 1,372 shared skills, 23 ms p50 search.
> [Architecture deep-dive →](https://caura.ai/blog/etoro-company-brain/)

<p align="center">
  <img src="static/images/caura-concept.png" alt="Caura — Fleet Memory that Compounds" width="700" />
</p>

<p align="center">
  <img src="static/images/caura-demo.gif" alt="Caura demo — write, recall, and governed cross-fleet memory in action" width="700" />
</p>

---

## Quick Start

### Try it locally — no API key, no signup

The fastest way to see Caura work. Standalone mode runs single-tenant with auth bypassed — start Caura, write a memory, and find it again. (It boots with dummy embeddings so there's nothing to configure; add an AI provider key for semantic search — see [Self-Hosted](#self-hosted-open-source) below.)

```bash
git clone https://github.com/caura-ai/caura.git
cd caura
cp .env.example .env && echo "IS_STANDALONE=true" >> .env   # single-tenant, no API key
docker compose up -d --wait                                 # Postgres + pgvector + Redis + API (~30s)
```

<!-- readme-quickstart-ci:start -->
```bash
# Write a memory — no API key needed
curl -X POST http://localhost:8000/api/v1/memories \
  -H "X-API-Key: standalone" -H "Content-Type: application/json" \
  -d '{"tenant_id": "default", "agent_id": "quickstart", "write_mode": "strong", "content":

... (truncated)