AI memory layer — one shared, persistent memory across every AI tool you connect.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
Manual Client & Custom JSON ConfigExpand JSON ▾
Client Config & Setup
Remote HTTPChoose your client or environment
Target File:
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Documentation Overview
Atlaso — remote MCP server
Atlaso is an AI memory layer: one shared, persistent memory across every AI tool you connect.
Tell it once in one tool, and it's already there in the next. Atlaso recalls the context that matters before each turn and captures the durable facts after — your decisions, your preferences, and where you left off.
This repository documents Atlaso's hosted MCP server. Atlaso is a managed service, so there is nothing to self-host and no server code here — you connect to the endpoint below and authorize in your browser.
- Endpoint:
https://mcp.atlaso.ai/mcp - Transport: Streamable HTTP
- Auth: OAuth 2.1 with dynamic client registration — your MCP client walks you through it; there are no API keys to paste
- Website: https://www.atlaso.ai
- Docs: https://docs.atlaso.ai
Connect
Any MCP client that supports remote servers can connect. Add
https://mcp.atlaso.ai/mcp as a connector and authorize in the browser when
prompted.
Claude Desktop / claude.ai — Settings → Connectors → Add custom connector → paste the endpoint → Connect → authorize.
Cursor, VS Code, and other MCP clients — add it as a remote MCP server:
Terminal-based tools (Claude Code, Codex, OpenCode, Antigravity) get a richer integration than MCP alone — automatic recall before each turn and automatic capture after, via hooks. One command sets all of them up:
That installs the atlaso CLI, links the machine (creating your account if you
don't have one), then asks which of your AI tools should share the memory.
Tools
| Tool | What it does |
|---|---|
recall(query, limit=5) | Search your memory for notes relevant to query. Returns a ranked list of {id, content}. Read-only. |
remember(text, polarity) | Save a durable note — a decision, preference, or gotcha. polarity is one of positive, open, cautionary, negative. Returns the new id. |
recent(limit=10) | List the most recent memories, newest first. Read-only. |
forget(id) | Permanently delete a memory by id. Destructive and not undoable. |
status() | Connection state, how many memories are stored and pending, and your memory health score. Read-only. |
Every recall carries a verdict on whether a memory is settled or contested, so the model isn't acting on shaky context.
Memory scopes
Memories are either personal (they follow you everywhere) or project (scoped to the repository or workspace you were in). Both are recalled automatically in the right place — you don't manage scopes by hand.
Privacy
Secrets are scrubbed before anything is stored. Data is encrypted in transit and at rest. Your memory is never used to train AI models and never sold. On the free plan it is never sent to any LLM at all. You can delete any single memory, or your whole account, at any time.
Pricing
Free for one device and one tool. Pro is $10/month for unlimited devices and tools sharing one memory, plus Ambient Memory, background enrichment, Ask your memory, and JSON export. Build is $25/month and adds a developer memory API.
Registry
Listed in the official MCP Registry as io.github.imashishkh21/atlaso. The
server.json in this repository is the published manifest.
Atlaso is a product of Atlaso Labs Inc. This repository is documentation for the hosted service; the service itself is not open source.
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Frequently Asked Questions about Atlaso Labs MCP
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