# ASR Memory (에사 AI) — Shared memory for AI tools MCP server

Shared memory for AI tools: save once, recall word for word from Claude, ChatGPT, Codex or Gemini.

## At a glance

ASR Memory (에사 AI) — Shared memory for AI tools is an MCP server in the AI & Memory category. It is hosted remotely and connects over HTTP, and declares no required credentials. It exposes 19 tools, including memory_save, memory_search and memory_card. It scores B (73/100) on the MCP Skills Hub health score as of Oct 28, 2026.

## Install

### How to install ASR Memory (에사 AI) — Shared memory for AI tools in Claude Code

1. Add the server

```bash
claude mcp add --transport http asr https://asrmemory.com/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. memory_save, memory_search, memory_card). It discovers them automatically.

### How to install ASR Memory (에사 AI) — Shared memory for AI tools 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": {
    "asr": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://asrmemory.com/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 ASR Memory (에사 AI) — Shared memory for AI tools in Cursor

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

```json
{
  "mcpServers": {
    "asr": {
      "url": "https://asrmemory.com/mcp"
    }
  }
}
```

2. Enable it

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

### How to install ASR Memory (에사 AI) — Shared memory for AI tools in Codex CLI

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

```toml
[mcp_servers.asr]
command = "npx"
args = ["-y", "mcp-remote", "https://asrmemory.com/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 ASR Memory (에사 AI) — Shared memory for AI tools in Windsurf

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

```json
{
  "mcpServers": {
    "asr": {
      "serverUrl": "https://asrmemory.com/mcp"
    }
  }
}
```

2. Reload

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

### How to install ASR Memory (에사 AI) — Shared memory for AI tools in Cline

1. Open Cline → MCP Servers → Configure

   Adds to cline_mcp_settings.json.

2. Add the server

```json
{
  "mcpServers": {
    "asr": {
      "type": "streamableHttp",
      "url": "https://asrmemory.com/mcp"
    }
  }
}
```

### How to install ASR Memory (에사 AI) — Shared memory for AI tools in VS Code

1. Create .vscode/mcp.json

```json
{
  "servers": {
    "asr": {
      "type": "http",
      "url": "https://asrmemory.com/mcp"
    }
  }
}
```

2. Start it

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

## Tools

- `memory_save` — Save a memory as written, with who saved it and when it happened
- `memory_search` — Search by meaning and keywords
- `memory_card` — Show one memory in full
- `memory_recall_daily` — Recall what happened on a date
- `wake_up` — Brief a new session on recent work
- `memory_stats` — Counts by drawer and tool
- `memory_retag` — Change a memory's drawer
- `memory_delete` — Move a memory to the trash
- `memory_trash` — List the trash
- `memory_restore` — Restore from the trash
- `memory_purge` — Permanently delete (asks first)
- `memory_export` — Export your memories as JSON Lines
- `secret_save` — Store and read an encrypted value
- `promise_start` — Track a goal day by day; only you mark the result
- `asr_send` — Send a task to another tool
- `asr_handoff` — Hand off unfinished work when a session ends
- `asr_inbox` — See and take tasks sent to you
- `asr_done` — Close a task with its result
- `asr_tidy` — Save a project status summary

Source repository: https://github.com/xjoanet/asr-memory-docs

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