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Atlaso Memory

Registre officiel IA et agents

Atlaso, the AI memory layer: one shared, persistent memory for every AI tool you connect.

Code source Site web Documentation

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http atlaso-memory 'https://mcp.atlaso.ai/mcp'
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "atlaso-memory": {
            "type": "http",
            "url": "https://mcp.atlaso.ai/mcp"
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Atlaso — remote MCP server
  2. Connect
  3. Tools
  4. Memory scopes
  5. Privacy
  6. Pricing
  7. Registry

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:

{
  "mcpServers": {
    "atlaso": {
      "url": "https://mcp.atlaso.ai/mcp"
    }
  }
}

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:

curl -fsSL https://atlaso.ai/install.sh | bash    # macOS / Linux
irm https://atlaso.ai/install.ps1 | iex           # Windows

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

ToolWhat 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.

Questions fréquentes

Qu'est-ce que Atlaso Memory ?

Atlaso, the AI memory layer: one shared, persistent memory for every AI tool you connect.

Comment installer Atlaso Memory ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http atlaso-memory 'https://mcp.atlaso.ai/mcp'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Atlaso Memory ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

Atlaso Memory est-il open source ?

Son code est public sur GitHub, mais le dépôt ne déclare pas de licence standard.

Qui maintient Atlaso Memory ?

Il est publié par atlaso-labs. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.