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Memory MCP

by @ragionex

Stores, recalls, updates, and deletes agent memories in permissioned Ragionex Vaults across sessions.

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Install Memory MCP

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": {
    "ragionex-memory-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@ragionex/memory-mcp@latest"
      ],
      "env": {
        "RAGIONEX_MEMORY_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 11 tools correctly ().

Overview

@ragionex/memory-mcp connects MCP-compatible agents to Ragionex Memory, a long-term context service organized into project-specific Vaults. Agents can recall saved information in plain language and manage memories as facts, decisions, preferences, and task outcomes change. It runs locally over MCP stdio and authenticates with a Ragionex API key. Reach for it when an agent needs persistent, shared, and permission-controlled context across sessions.

Use cases

  • Recall project decisions across agent sessions
  • Save user preferences and working conventions
  • Update memories when requirements or facts change
  • Separate context for different projects with Vaults
  • Share selected project memory with teammates

Key features

  • Natural-language memory recall
  • Persistent cross-session memory
  • Vault-based project separation
  • Key-based permissions and sharing
  • Version history and 30-day trash
  • Local MCP stdio transport

Tools11

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

Verified live~2.9k 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

Recent health check succeeded.

What it can do

From the 11 tools this server returned when we ran it; 11 declare their own safety hints.

Can delete or modify data · 3Makes network requests · 2Read-only tools · 8
Network at startup3 connections
Files written at startupNone
Install scriptsNone
npm provenanceNot published
Package age138 days
Maintainers1

Observed 2026-11-09 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 4d ago via OSV.dev · @ragionex/memory-mcp@latest (npm)

Adoption & maintenance

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

GitHub stars5Stargazers on the source repository.
npm downloads1.1kPackage 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 exposed11Callable tools this server registers over MCP.

How Memory MCP works

What @ragionex/memory-mcp does

@ragionex/memory-mcp gives AI agents access to Ragionex Memory, a long-term memory service for retaining useful context between sessions. Agents can store project facts, decisions, preferences, documents, and results from earlier attempts, then retrieve relevant records using natural-language questions.

Memory is organized into Vaults, such as one Vault per project. Vaults can be shared with teammates and their agents, with permissions controlling what each key can do. This makes the server suitable for separating projects or limiting access between agents.

Ragionex returns memories as they were saved rather than generating a replacement answer from them. Changes update existing records instead of leaving conflicting duplicates, and incorrect records can be removed. Earlier versions remain available for 30 days, while deleted memories stay in a trash for the same period.

How it works

The package runs as a local MCP server using stdio. An MCP client starts it with Node.js and communicates with it through the standard input and output streams. Authentication uses an API key associated with the Ragionex account and agent or client configuration.

Agents can ask for relevant memories in ordinary language, including when the wording differs from the original saved text. The setup process can also add guidance to an agent's global instructions so the agent knows when to recall and save context. Clients that only receive the MCP tools can still use the server, but they do not automatically receive that additional memory guidance.

Setup and configuration

Node.js 18 or newer is required. The package can be launched without a global install through npx:

Terminal
npx -y @ragionex/memory-mcp@latest install

On Windows, use npx.cmd instead. The interactive installer helps select an agent, opens a sign-in flow, and asks for a one-time code. It then adds a ragionex-memory-mcp entry to the selected MCP configuration and creates an agent-specific API key without displaying the key.

For clients configured manually, create a key through the Ragionex key page and set RAGIONEX_MEMORY_API_KEY in the MCP server environment. The command uses npx -y @ragionex/memory-mcp@latest on macOS and Linux; Windows configurations invoke npx through cmd.

Manual setup is also available for agents with a global instructions file. The installer can add a marked Ragionex Memory section, preserve the surrounding content, and back up the file before its first change. The setup supports an uninstall command for removing its changes.

Tools and capabilities

  • Recall memories with natural-language queries.
  • Save decisions, preferences, project facts, documents, and work outcomes.
  • Update records when information changes.
  • Delete memories that are no longer correct.
  • Organize memory in separate Vaults.
  • Share Vaults with teammates and their agents through key-based permissions.
  • Preserve earlier versions and deleted records for 30 days.

Limitations and notes

The server provides MCP tools to clients, but automatic memory behavior depends on the client and its instruction support. Claude Desktop, Cursor, Cline, and other clients that run local MCP servers can use the tools with a manually configured API key. A client with a global instructions file can use the manual setup to receive the additional recall-and-save guidance.

The setup flow requires network access and user sign-in. The one-time code must be supplied by the account holder; the setup instructions direct the agent not to open the approval link itself. After installation, the client generally needs to be fully restarted in a new session before the setup is ready to use.

Read the full README View source on GitHub

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Frequently Asked Questions about Memory MCP

@ragionex/memory-mcp is an MCP server that connects AI agents to Ragionex Memory for persistent context across sessions. Its main capabilities cover recalling memories in natural language, saving useful information, updating changed records, and deleting incorrect ones. Memory is organized in permissioned Vaults that can be shared across projects and teams.

Install it with `npx -y @ragionex/memory-mcp@latest install` on macOS or Linux, or use `npx.cmd` on Windows. The interactive setup selects an agent, handles sign-in and a one-time code, then adds the MCP configuration. Node.js 18 or newer is required.

Yes, @ragionex/memory-mcp works with Cursor when configured as a local MCP server. Create a Ragionex API key, add the server to Cursor's user-global MCP configuration, and set `RAGIONEX_MEMORY_API_KEY` in its environment.

Set the key in the MCP server environment as `RAGIONEX_MEMORY_API_KEY`. For manual client configuration, create a key through the Ragionex keys page and add it alongside the `npx` command in the client's MCP settings.

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