# WorkingMemory MCP server

Persistent personal memory for AI assistants — save, search, and recall across every MCP client.

## At a glance

WorkingMemory is an MCP server in the Web & Search category. It is hosted remotely and connects over HTTP, and declares no required credentials. It exposes 4 tools, including save_memory, search_memory and manage_memory. It scores D (33/100) on the MCP Skills Hub health score as of Oct 28, 2026.

## Install

### How to install WorkingMemory in Claude Code

1. Add the server

```bash
claude mcp add --transport http memory https://app.workingmemory.ai/mcp
```

2. Verify it's connected

```bash
claude mcp list
```

3. Sharing it with your team?

   Add `--scope project` to write it to .mcp.json in the repository root, which you can commit (with the secrets left as environment variables).

4. Use it in a session

   Ask Claude to use the tools this server exposes (e.g. save_memory, search_memory, manage_memory). It discovers them automatically.

### How to install WorkingMemory in Claude Desktop

1. Open your MCP config

   macOS: ~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

2. Add this server

```json
{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://app.workingmemory.ai/mcp"
      ]
    }
  }
}
```

3. Why the wrapper?

   This is a remote (HTTP) server and Claude Desktop only launches local processes, so mcp-remote proxies the connection. It will open a browser window if the server needs OAuth.

4. Restart Claude Desktop

   The tools appear under the 🔌 menu once the app reloads.

### How to install WorkingMemory in Cursor

1. Create / edit .cursor/mcp.json in your project

```json
{
  "mcpServers": {
    "memory": {
      "url": "https://app.workingmemory.ai/mcp"
    }
  }
}
```

2. Enable it

   Cursor Settings → MCP → toggle the server on. Tools become available to the Composer/Agent.

### How to install WorkingMemory in Codex CLI

1. Add to ~/.codex/config.toml

```toml
[mcp_servers.memory]
command = "npx"
args = ["-y", "mcp-remote", "https://app.workingmemory.ai/mcp"]
```

2. Why the wrapper?

   Codex runs MCP servers as local processes, so mcp-remote bridges this HTTP endpoint to stdio.

3. Run Codex

   Codex loads MCP servers from config.toml on startup and exposes their tools to the agent.

### How to install WorkingMemory in Windsurf

1. Edit ~/.codeium/windsurf/mcp_config.json

```json
{
  "mcpServers": {
    "memory": {
      "serverUrl": "https://app.workingmemory.ai/mcp"
    }
  }
}
```

2. Reload

   Windsurf → Cascade → refresh MCP servers. Cascade can now call the tools.

### How to install WorkingMemory in Cline

1. Open Cline → MCP Servers → Configure

   Adds to cline_mcp_settings.json.

2. Add the server

```json
{
  "mcpServers": {
    "memory": {
      "type": "streamableHttp",
      "url": "https://app.workingmemory.ai/mcp"
    }
  }
}
```

### How to install WorkingMemory in VS Code

1. Create .vscode/mcp.json

```json
{
  "servers": {
    "memory": {
      "type": "http",
      "url": "https://app.workingmemory.ai/mcp"
    }
  }
}
```

2. Start it

   VS Code shows a ▶ Start action above the server entry. Agent mode (Copilot Chat) can then use the tools.

## Tools

- `save_memory` — Save a thought, insight, fact, or todo to the user's Working Memory. The text is parsed and stored as one or more structured memory items, searchable a moment later via search_memory. Also use this when the user pastes memories or notes brought from another assistant — pass the full pasted text; it is split into individual memories automatically.
- `search_memory` — Search the user's Working Memory for relevant past notes and facts. Use this when the user references something they may have stored earlier, or to find related context before answering. Always include your conversation id in client.conversation_id.
- `manage_memory` — Manage an existing memory item. Currently supports deleting a memory by id (soft delete — recoverable for 30 days). Use search_memory to find the id first.
- `capture_memory` — Capture durable facts from a task you just completed (drafting an email, summarizing a document, making a decision), as a byproduct — the user does nothing. Pass the task output/content; durable facts are extracted and stored automatically. Always include your conversation id in client.conversation_id. Returns immediately; extraction happens in the background.

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Source: https://mcp-skills-hub.vercel.app/mcps/ai-workingmemory-memory · MCP Skills Hub · data as of 2026-10-28T12:31:05Z