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  1. Home
  2. 🧠 Knowledge & Memory
  3. Atlaso Labs MCP
Atlaso Labs MCP logo
Health: ActiveRecent health check succeeded.Last checked 10/12/2026, 4:02:42 AM

Atlaso Labs MCP

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View RepositoryVisit Website
memoryknowledgeremote-mcpoauth

Shares persistent personal and project memory across connected AI tools through a hosted MCP endpoint.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "mcp-3": {
      "url": "https://mcp.atlaso.ai/mcp"
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

Atlaso Labs MCP MCP server provides shared, persistent memory for connected AI tools through a hosted remote endpoint. It uses Streamable HTTP and OAuth 2.1 with browser-based authorization, so clients connect without pasted API keys or local hosting. Agents can search, save, list, inspect, and delete memories, including personal and project-scoped context. Reach for it when decisions, preferences, and work context need to carry across multiple AI tools.

Use cases

•Share decisions across multiple AI assistants
•Recall project context in a new workspace
•Store preferences for later conversations
•Review or delete recent memories
•Check memory connection and health status

Key features

•Hosted Streamable HTTP endpoint
•OAuth 2.1 browser authorization
•Personal and project memory scopes
•Ranked memory recall with verdicts
•Durable notes with polarity
•Memory status and deletion tools

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Atlaso Labs MCP.

Extracted Tool Capabilities
Hosted Streamable HTTP endpoint
OAuth 2.1 browser authorization
Personal and project memory scopes
Ranked memory recall with verdicts
Durable notes with polarity
Memory status and deletion tools

How Atlaso Labs MCP works

What the Atlaso Labs MCP MCP server does

Atlaso Labs MCP MCP server connects MCP-compatible AI clients to Atlaso's hosted memory service. It keeps durable notes such as decisions, preferences, and project context available across connected tools. Personal memories follow the user, while project memories are associated with the repository or workspace where they were created.

The service is intended for situations where an agent needs continuity beyond a single conversation or application. Atlaso recalls relevant context before a turn and can capture durable information afterward. Recall results include a verdict indicating whether a memory is settled or contested, helping the model distinguish established information from uncertain context.

How it works

The server is accessed remotely at https://mcp.atlaso.ai/mcp using Streamable HTTP. Authentication uses OAuth 2.1 with dynamic client registration. The MCP client handles browser authorization, and the connection does not require an API key pasted into configuration.

Atlaso Labs MCP MCP server exposes memory operations directly to the client. recall searches stored notes and returns ranked results, remember creates a durable note with a polarity, and recent lists the newest memories. forget permanently removes a memory by ID, while status reports connection state, memory counts, and a memory health score.

The repository documents the hosted service rather than providing server code to run locally. Terminal integrations can also be installed with Atlaso's shell or PowerShell installer, which sets up the atlaso CLI, links the machine, and lets the user select supported AI tools for shared memory.

Setup and configuration

Add the remote URL as an MCP connector in a compatible client and authorize in the browser when prompted. A generic configuration has this shape:

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

Claude Desktop and claude.ai can use the custom connector settings. Cursor, VS Code, and other remote-MCP clients can use the URL in their MCP configuration. Claude Code, Codex, OpenCode, and Antigravity can use the provided installer for CLI-oriented hooks that add automatic recall and capture beyond the MCP connection itself.

No environment variables or API keys are documented as required. Account creation or machine linking occurs during authorization or the CLI setup process.

Tools and capabilities

  • recall(query, limit=5): searches memory and returns ranked {id, content} results.
  • remember(text, polarity): stores a note with positive, open, cautionary, or negative polarity.
  • recent(limit=10): lists recent memories in newest-first order.
  • forget(id): permanently deletes one memory and cannot undo the operation.
  • status(): reports connection status, stored and pending memory counts, and a health score.

Secrets are scrubbed before storage. Data is encrypted in transit and at rest, and the README states that memory is not used to train AI models or sold. Individual memories or the entire account can be deleted.

Limitations and notes

Atlaso is a managed service; this repository does not contain self-hostable server code. Use therefore depends on access to the hosted endpoint and browser-based OAuth authorization. Memory scope is assigned automatically as personal or project context rather than being managed manually.

The free plan supports one device and one tool. Paid plans add broader device and tool sharing, with additional features varying by plan. The Build plan includes a developer memory API. forget is destructive, so clients should use it only when permanent deletion is intended.

Read the full README →View source on GitHub →

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Reviews

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Frequently Asked Questions about Atlaso Labs MCP

Atlaso Labs MCP is an MCP server that connects AI tools to Atlaso’s hosted persistent memory service. Its main tools are recall, remember, recent, forget, and status, allowing agents to search relevant notes, save durable context, inspect recent memories, delete entries, and check connection and memory health.

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand ▾
TransportSSE (Remote)
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue, LM Studio
Last updatedOct 7, 2026
16/16 checks healthy over the last 63d
Views0
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Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 27, 2026
37Quality signal: Fair · 37/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity2/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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