Atlaso Memory

ai.atlasoPublished by atlaso.aiOfficial publisherv1.0.2Updated Oct 26, 2026

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

VerifiedStreamable HTTPWeb executableProductivity & WorkflowKnowledge & Memory

Overview

AI-generated overview

Hosted memory layer that gives any MCP client one shared, persistent memory of decisions, preferences and context across AI tools.

What you can do
  • Search stored memories by query and get a ranked list of notes with a verdict on whether each is settled or contested
  • Save durable notes such as decisions, preferences or gotchas, tagged by polarity
  • List the most recent memories, newest first
  • Permanently delete a memory by id
  • Check connection state, how many memories are stored or pending, and a memory health score
When to use it
Useful when you work across several MCP clients or coding tools and want context, decisions and preferences to carry over between them instead of being re-explained in each chat.
Requirements
A remote MCP client that supports Streamable HTTP; connect to the hosted endpoint and authorize through OAuth 2.1 with dynamic client registration, so no API keys are pasted. Nothing is self-hosted. Terminal tools can optionally install a CLI for automatic recall and capture. Free plan covers one device and one tool; paid plans for more.
Before you install
The forget tool permanently deletes a memory and cannot be undone. Memories are stored on a third-party hosted service, so anything the assistant saves leaves your machine; the README says secrets are scrubbed and data is encrypted, but review what gets remembered. Paid tiers cost $10 or $25 per month. The optional install script creates an account and links the machine.

Installation

In SourceWeft

  1. Open Atlaso Memory in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.atlaso%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "atlaso-memory": {
      "type": "http",
      "url": "https://mcp.atlaso.ai/mcp"
    }
  }
}

README

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

Why this exists

Claude Desktop, Zed, Cline and other MCP clients have no memory of their own that reaches your coding tools. This hosted server gives any MCP client the same memory your coding tools share: decisions made in long chats, research and notes, preferences that should follow you. Memory works when the model calls the tools (remember, recall, forget); a skill can make that routine. Add https://mcp.atlaso.ai/mcp as a connector and sign in. Claude Desktop · Any MCP tool

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:

json
{  "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:

bash
curl -fsSL https://atlaso.ai/install.sh | bash    # macOS / Linuxirm 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.

Source: README.md at commit 050849e

Tools

0
This server asks you to sign in, so SourceWeft could not read its tools without an account and has not indexed them. What a connected account sees can depend on that account and its permissions.

Version history

2
  1. v1.0.2LatestOct 26, 2026
  2. v1.0.1Sep 16, 2026

Score

75% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.

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Atlaso

Published by GitHub account imashishkh21

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STDIODesktop only
DatabasesNot validated yetOct 25, 2026