atlaso.ai

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# Atlaso - AI-Friendly robots.txt
# We want maximum AI visibility — allow all search and citation bots

# === Standard Search Engines ===
User-agent: Googlebot
Allow: /

User-agent: Bingbot
Allow: /

# === OpenAI (ChatGPT) ===
User-agent: GPTBot
Allow: /

User-agent: OAI-SearchBot
Allow: /

User-agent: ChatGPT-User
Allow: /

# === Anthropic (Claude) ===
User-agent: anthropic-ai
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: claude-web
Allow: /

# === Perplexity ===
User-agent: PerplexityBot
Allow: /

User-agent: Perplexity-User
Allow: /

# === Google Gemini ===
User-agent: Google-Extended
Allow: /

# === Apple / Siri ===
User-agent: Applebot
Allow: /

User-agent: Applebot-Extended
Allow: /

# === Other AI Search ===
User-agent: DuckAssistBot
Allow: /

User-agent: YouBot
Allow: /

User-agent: MistralAI-User
Allow: /

User-agent: Amazonbot
Allow: /

User-agent: GrokBot
Allow: /

User-agent: xAI-Grok
Allow: /

# === Formerly blocked, now allowed (maximum AI visibility) ===
User-agent: CCBot
Allow: /

User-agent: Bytespider
Allow: /

# === Default: allow everything ===
User-agent: *
Allow: /

# === Content-Signal (https://contentsignals.org) ===
# Affirmative AI-usage signal, matching docs.atlaso.ai
Content-Signal: ai-train=yes, search=yes, ai-input=yes

# === Sitemap ===
Sitemap: https://www.atlaso.ai/sitemap.xml

# === LLM / Agent discovery (https://llmstxt.org) ===
# Plain-text indexes optimized for AI ingestion.
# llms.txt: https://www.atlaso.ai/llms.txt (mirrored at /.well-known/llms.txt)
# Full documentation for LLMs lives on the docs subdomain:
# docs index: https://docs.atlaso.ai/llms.txt
# full docs:  https://docs.atlaso.ai/llms-full.txt

# Atlaso

> The memory layer for the AI era. Atlaso gives your AI tools a shared,
> persistent memory: it captures what matters as you work, recalls it before
> every prompt, and carries it across Claude Code, Cursor, Codex, Claude
> Desktop, OpenCode, and Antigravity (ChatGPT and Meta AI support coming).

Atlaso is a hosted service with thin connectors per tool.
Install with one command — no account needed first, because the command opens
the browser to create it:
  macOS/Linux:  curl -fsSL https://atlaso.ai/install.sh | bash
  Windows:      irm https://atlaso.ai/install.ps1 | iex
That installs the atlaso CLI, links the machine, then asks which of your AI
tools should share the memory and wires up each one. GUI chat apps (Claude
Desktop, claude.ai, any MCP client) need no terminal — they add
https://mcp.atlaso.ai/mcp as a connector and authorize in the browser. You can
also sign in at app.atlaso.ai/sign-in first if you prefer the dashboard.
Free plan: 1 device + 1 active tool, automatic capture & recall, personal +
per-project memory scopes, cloud sync, unlimited memories, web dashboard.
Pro ($10/month, monthly-only, no trial): unlimited devices & tools sharing
one memory, Ambient Memory delivered in Claude Code and Codex, automatic
background refinement, Ask-your-memory, and memory downloads as JSON,
Markdown, AI context or CSV, or print to PDF. Insights is coming soon for Pro.
Build and Teams are planned, not on sale: no price and no date. Build is
planned to bring Atlaso memory to your own app or hardware, with a private
memory per end-user; Teams is planned around shared team memory, handoffs and
catch-up. Keys, tokens and passwords are redacted before a memory is stored,
wherever Atlaso can recognise them; memory is never trained on or sold.

## Product

- [Home](https://www.atlaso.ai): what Atlaso does and how it works
- [Pricing](https://www.atlaso.ai/pricing): Free plan + Pro at $10/month, with Build and Teams planned — full comparison
- [Pricing for AI agents](https://www.atlaso.ai/pricing.md): the same plans, limits, and billing terms as plain markdown
- [Install Atlaso](https://docs.atlaso.ai/install): the one-line install for macOS, Linux and Windows, and exactly what it does
- [CLI reference](https://docs.atlaso.ai/cli): every atlaso command — connect, setup, status, sync, unlink, disconnect
- [Docs & Help](https://docs.atlaso.ai): per-tool setup, the one-active-tool rule on Free, plans & billing behavior, troubleshooting, GUI connectors, privacy
- [Docs index for LLMs](https://docs.atlaso.ai/llms.txt): machine-readable docs index (per-page .md links)
- [Full docs for LLMs](https://docs.atlaso.ai/llms-full.txt): the complete documentation as one plain-text file
- [What is an AI memory layer?](https://www.atlaso.ai/what-is-an-ai-memory-layer): the definitional explainer
- [Atlaso vs mem0](https://www.atlaso.ai/vs/mem0): reader-matched benchmark comparison, honest limits included
- [Atlaso vs ChatGPT memory](https://www.atlaso.ai/vs/chatgpt-memory): built-in memory vs a cross-tool memory layer, from official docs
- [Atlaso vs Claude memory](https://www.atlaso.ai/vs/claude-memory): claude.ai memory, Claude Code memory, and what a shared layer adds
- [Atlaso vs Zep](https://www.atlaso.ai/vs/getzep): Zep is agent-memory infrastructure developers build on; Atlaso is a product you install for the tools you already use
- [Contact](https://www.atlaso.ai/contact): message the team (support@atlaso.ai)

## Memory for your tool

- [Claude Code](https://www.atlaso.ai/for/claude-code): full automatic recall + capture on every turn
- [Cursor](https://www.atlaso.ai/for/cursor): automatic capture; recall via a generated rules file
- [Codex](https://www.atlaso.ai/for/codex): full automatic memory in Codex CLI and Desktop
- [Claude Desktop](https://www.atlaso.ai/for/claude-desktop): memory via custom connector (MCP) — no terminal needed
- [OpenCode](https://www.atlaso.ai/for/opencode): full automatic memory via a local plugin the CLI installs
- [Antigravity](https://www.atlaso.ai/for/antigravity): full automatic memory in IDE and CLI
- [Any MCP tool](https://docs.atlaso.ai/tools/custom-mcp): connect any MCP-capable client (Zed, Cline, …) via https://mcp.atlaso.ai/mcp

## Lab

- [Lab](https://www.atlaso.ai/lab): published research on AI memory, with full methodology and raw run logs
- [Atlaso vs mem0 benchmark](https://www.atlaso.ai/lab/memory-benchmark): reader-matched head-to-head on LongMemEval-S (n=500) — Atlaso +6.6pp over mem0 (p≈0.007), three independent judges, losses published
- [Giving AI a subconscious](https://www.atlaso.ai/lab/ai-subconscious): the Ambient Memory essay
- [Adaptive stigmergy gates](https://www.atlaso.ai/lab/adaptive-stigmergy-gates): when multi-agent coordination should turn on
- [Where the memory lift comes from](https://www.atlaso.ai/lab/growing-field-substrate): 94% retrieval, 6% format

## Legal

- [Privacy Policy](https://www.atlaso.ai/privacy)
- [Terms of Service](https://www.atlaso.ai/terms)
- [Refund & Cancellation Policy](https://www.atlaso.ai/refunds)