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Purmemo

Shared AI memory for saving conversations, recalling topics, loading user context, and tracking changes across MCP clients.

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Install Purmemo

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "purmemo": {
      "command": "npx",
      "args": [
        "-y",
        "purmemo-mcp@latest"
      ],
      "env": {
        "PURMEMO_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Automated check passed— started and listed 5 tools correctly (Today).

Overview

The purmemo MCP server connects AI clients to a persistent memory service for saving conversations, searching memories, loading user context, and reviewing dated changes. It exposes five default MCP tools and can add session-search or administrative tools through environment flags. Use it when context needs to carry across Claude, Cursor, Windsurf, Zed, or other MCP-compatible workflows. Hosted streamable HTTP and local npx-based setups are available.

Use cases

  • Save conversations for reuse across AI sessions
  • Recall project decisions with natural-language searches
  • Load personal and project context at session start
  • Review how project or person information changed over time
  • Search raw transcripts from past AI sessions

Key features

  • Persistent cross-session conversation memory
  • Natural-language memory recall
  • Automatic user-context loading
  • Dated change history for remembered subjects
  • Optional past-session transcript search
  • Hosted and local MCP connection modes

Tools5

What Purmemo lets your agent do. Expand a tool for its parameters.

Verified live~3.4k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

8/8 checks healthy over the last 50d

What it can do

From the 5 tools this server returned when we ran it; 5 declare their own safety hints.

Makes network requests · 4Read-only tools · 5
Network at startup4 connections
Files written at startup1
Install scriptspostinstall
npm provenanceSigned build
Package age435 days
Maintainers2

Observed 2026-10-28 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 17d ago via OSV.dev · purmemo-mcp@latest (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars2Stargazers on the source repository.
npm downloads1.3kPackage downloads in the last 30 days.
Last commit5d agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed5Callable tools this server registers over MCP.

How Purmemo works

What purmemo does

purmemo provides shared memory for AI-assisted work. Conversations can be saved and later searched using natural-language topics, while user context such as a role, projects, or technology stack can be loaded at the start of a session. The service also reports how information about a person, project, or other subject changed over time.

The connector is designed for use across supported MCP clients, so memories are available beyond a single conversation or application. A dashboard at app.purmemo.ai can be used to view and manage stored memories. The platform offers a free plan with 50 recalls per month and unlimited saves, plus a paid plan with unlimited recalls and saves.

How it works

The server can run locally through the purmemo-mcp npm package or connect through purmemo's hosted streamable HTTP endpoint. Local operation authenticates with a purmemo API key; the hosted Claude Desktop configuration uses OAuth during first use. The installation script can install Node.js when needed, configure the purmemo command, and guide sign-in through a browser.

Five tools are enabled by default: saving a conversation, recalling memories, retrieving memory details, checking what changed, and loading user context. The package also supports slash-command-style workflows such as /save, /recall <topic>, and /context when used through a compatible client experience.

Setup and configuration

For macOS or Linux, run the install script with curl -fsSL https://app.purmemo.ai/install | sh. Windows users can run the PowerShell installer with irm https://app.purmemo.ai/install.ps1 | iex. Then run purmemo, complete browser sign-in, and restart Claude Desktop or Claude Code.

With Node.js already installed, install the package globally using npm install -g purmemo-mcp && purmemo, or initialize it once with npx purmemo-mcp@latest init.

Claude Desktop can use the hosted endpoint https://mcp.purmemo.ai/mcp/messages with the streamable-http transport. For local configurations, run npx -y purmemo-mcp and provide PURMEMO_API_KEY. The README includes equivalent local configuration examples for Cursor, Windsurf, and Zed.

Optional flags extend the exposed tool set. PURMEMO_SESSIONS_BETA=1 adds search_past_sessions, which searches raw transcripts through the configured purmemo-next service. PURMEMO_ADMIN=1 adds investigation and acknowledged-error tools. PURMEMO_LEGACY_TOOLS=1 exposes paused legacy tools that respond with replacement guidance.

Tools and capabilities

The default MCP tool set includes:

  • save_conversation for storing a conversation.
  • recall_memories for searching saved memories.
  • get_memory_details for retrieving a specific memory.
  • what_changed for viewing dated changes to a subject.
  • get_user_context for loading identity and current-work context.

The sessions beta adds search_past_sessions for transcript searches. Admin mode adds get_acknowledged_errors, save_investigation_result, and get_investigations. Legacy mode exposes paused tools such as artifact, snapshot, workflow, sharing, task, and test-result operations; those tools indicate what to use instead.

The MCP connector code is MIT licensed, while the purmemo platform, API, and backend are proprietary.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Purmemo

purmemo is an MCP server that connects Claude Desktop, Claude Code, Cursor, Windsurf, Zed, and other MCP clients to shared AI memory. Its main tools save conversations, recall memories, retrieve memory details, report what changed, and load user context for new sessions.

Install it with the platform script or npm, then run `purmemo` and complete browser sign-in. macOS and Linux use the provided curl installer, Windows uses the PowerShell installer, and existing Node.js users can run `npm install -g purmemo-mcp && purmemo` or `npx purmemo-mcp@latest init`.

Configure Claude Desktop with either purmemo's hosted streamable HTTP endpoint or a local npx command. The hosted option uses `https://mcp.purmemo.ai/mcp/messages` and OAuth; the local option runs `npx -y purmemo-mcp` and supplies `PURMEMO_API_KEY`. Restart Claude Desktop after changing its configuration.

Yes, purmemo works with Cursor through its MCP configuration. Add a local `npx -y purmemo-mcp` server entry to `~/.cursor/mcp.json` and set `PURMEMO_API_KEY`, then use the client to access the default memory tools.

Yes, enabling `PURMEMO_SESSIONS_BETA=1` adds the `search_past_sessions` tool. It searches raw transcripts of past AI sessions for content that was said or decisions that were made.

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