# MemoryPlugin MCP server

Give every AI you use one shared, permanent memory. Store once, recall in whichever AI you open.

## At a glance

MemoryPlugin is an MCP server in the AI & Memory category. It is hosted remotely and connects over HTTP, and declares no required credentials. It exposes 14 tools, including store_memory, list_buckets and create_bucket. It scores D (33/100) on the MCP Skills Hub health score as of Oct 28, 2026.

## Install

### How to install MemoryPlugin in Claude Code

1. Add the server

```bash
claude mcp add --transport http memory https://www.memoryplugin.com/api/mcp/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. store_memory, list_buckets, create_bucket). It discovers them automatically.

### How to install MemoryPlugin 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://www.memoryplugin.com/api/mcp/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 MemoryPlugin in Cursor

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

```json
{
  "mcpServers": {
    "memory": {
      "url": "https://www.memoryplugin.com/api/mcp/mcp"
    }
  }
}
```

2. Enable it

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

### How to install MemoryPlugin in Codex CLI

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

```toml
[mcp_servers.memory]
command = "npx"
args = ["-y", "mcp-remote", "https://www.memoryplugin.com/api/mcp/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 MemoryPlugin in Windsurf

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

```json
{
  "mcpServers": {
    "memory": {
      "serverUrl": "https://www.memoryplugin.com/api/mcp/mcp"
    }
  }
}
```

2. Reload

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

### How to install MemoryPlugin 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://www.memoryplugin.com/api/mcp/mcp"
    }
  }
}
```

### How to install MemoryPlugin in VS Code

1. Create .vscode/mcp.json

```json
{
  "servers": {
    "memory": {
      "type": "http",
      "url": "https://www.memoryplugin.com/api/mcp/mcp"
    }
  }
}
```

2. Start it

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

## Tools

- `store_memory` — Save information to the user's MemoryPlugin account. MemoryPlugin lets users build persistent memory across AI conversations. WHEN TO USE: When the user asks to remember something, or confirms that a specific fact, preference, decision, or project detail from the conversation should be kept for later. Save only that item. Ask the user which bucket to save to if unclear. Buckets are organizational 
- `list_buckets` — List the user's memory buckets. Buckets are organizational folders for memories (e.g., 'Work', 'Personal', 'Health').
- `create_bucket` — Create a new bucket to organize memories. Buckets are folders like 'Work', 'Personal', 'Health'. Ask the user for a name if not specified.
- `get_memories_and_buckets` — Retrieve the user's saved memories from MemoryPlugin, optionally filtered by bucket. Also returns the list of available buckets. Use when the user asks what you know about them or refers to something they saved earlier.
- `list_bucket_categories` — List AI-generated categories within a bucket. When users activate Smart Memory, their memories are automatically organized into topic-based categories. Returns for each category: - name: Category title - summary: Dense overview of core facts, preferences, current projects, key context (~200 words) - additionalInfo: Lists specific topics available in this category and suggests when to load the full
- `list_category_memories` — Get all memories within a specific Smart Memory category. Use when a category's summary (from list_bucket_categories) indicates it's relevant to the current conversation. The categoryId persists across conversations.
- `search_memories` — Search the user's saved memories using hybrid semantic + keyword search. Returns matching memories ranked by relevance. MemoryPlugin stores memories the user wants to persist across AI conversations. Use when looking for specific saved information.
- `search_uploaded_files` — Search documents the user has uploaded to their MemoryPlugin document library (not files uploaded directly to this conversation). MemoryPlugin file buckets store documents persistently across all AI chats. Returns relevant text passages with source file and page info. Use when: - User explicitly mentions their MemoryPlugin documents - User asks about "my files" or "my documents" and there are no f
- `get_conversation_summary` — Get details of a specific past conversation. For short conversations (<5K tokens), returns the full transcript. For longer conversations, returns an AI-generated summary. Use when the user wants to dive deeper into a conversation returned by recall_chat_history. Requires the conversationId from that tool's sources array.
- `get_full_conversation` — Get the complete transcript of a specific past conversation. Returns all messages in the conversation without summarization. Use when you need the raw conversation content. Requires the conversationId from recall_chat_history's sources array.
- `export_conversation` — Download the complete transcript of a past conversation as a machine-readable JSON file. Returns a temporary download URL (expires in 15 minutes, no auth needed) that you fetch yourself to get the full conversation as structured messages (role, content, timestamp). Use when a transcript is too long to read inline, or when you need it as a file for analysis or scripting. To read a short transcript 
- `recall_chat_history` — Search and synthesize context from the user's past AI conversations that they have synced into their MemoryPlugin account. WHEN TO USE: When the user asks about their past decisions, patterns, preferences, relationships, projects, or a specific earlier conversation. HOW TO USE: - For simple lookups: a single query is fine - For complex/multifaceted topics: use parallel queries (via 'queries' array
- `update_or_move_memories` — Edit a single memory's text or bucket, or move multiple memories to a different bucket. WHEN TO USE: When the user wants to correct, update, or reorganize their saved memories. Single memory: provide memoryId with optional text and/or bucketId/bucketName. Bulk move: provide memoryIds array with bucketId or bucketName. Bucket can be specified by ID (number) or name (string). If a name is given and 
- `chat_history_overview` — Returns an AI-generated overview of the user, built from the chat history they have synced into their MemoryPlugin account. Use when the user asks what you know about them or asks you to load their background. If no overview exists yet, the user can generate one from their MemoryPlugin dashboard.

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