# MemoryRouter MCP server

Persistent AI memory shared across Claude, ChatGPT, coding agents, and compatible MCP clients.

## At a glance

MemoryRouter is an MCP server in the AI & Memory category. It is hosted remotely and connects over HTTP, and declares no required credentials. It exposes 10 tools, including search_memories, date_search_memories and store_memory. It scores D (33/100) on the MCP Skills Hub health score as of Oct 28, 2026.

## Install

### How to install MemoryRouter in Claude Code

1. Add the server

```bash
claude mcp add --transport http memoryrouter https://mcp.memoryrouter.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. search_memories, date_search_memories, store_memory). It discovers them automatically.

### How to install MemoryRouter 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": {
    "memoryrouter": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.memoryrouter.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 MemoryRouter in Cursor

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

```json
{
  "mcpServers": {
    "memoryrouter": {
      "url": "https://mcp.memoryrouter.ai/mcp"
    }
  }
}
```

2. Enable it

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

### How to install MemoryRouter in Codex CLI

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

```toml
[mcp_servers.memoryrouter]
command = "npx"
args = ["-y", "mcp-remote", "https://mcp.memoryrouter.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 MemoryRouter in Windsurf

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

```json
{
  "mcpServers": {
    "memoryrouter": {
      "serverUrl": "https://mcp.memoryrouter.ai/mcp"
    }
  }
}
```

2. Reload

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

### How to install MemoryRouter in Cline

1. Open Cline → MCP Servers → Configure

   Adds to cline_mcp_settings.json.

2. Add the server

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

### How to install MemoryRouter in VS Code

1. Create .vscode/mcp.json

```json
{
  "servers": {
    "memoryrouter": {
      "type": "http",
      "url": "https://mcp.memoryrouter.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

- `search_memories` — Use this when the user asks about a prior decision, preference, person, project, or other fact that may be in their connected MemoryRouter vault. Semantically searches only the OAuth-selected vault and does not modify it. Tier guide: tier 3 holds the highest-level consolidated reflections (identity, principles, what matters most), tier 2 holds reflections of specific meaningful events, tier 1 hold
- `date_search_memories` — Use this to retrieve memories from a specific time window, for questions like 'what happened last week' or 'most important things this month or lately'. Tier guide: tier 3 holds the highest-level consolidated reflections (identity, principles, what matters most), tier 2 holds reflections of specific meaningful events, tier 1 holds raw verbatim memories. Match filters to the question. Time-bounded 
- `store_memory` — Use this only when the user explicitly asks to remember something or confirms a proposed durable fact. Saves concise user-approved content to the OAuth-selected vault; do not use it for silent conversation capture.
- `memory_status` — Use this when the user asks whether MemoryRouter is connected, which opaque vault binding is active, or how many memories/tokens the connected vault contains. Does not reveal the memory key.
- `forget_all_memories` — Use this only after the user explicitly requests a full-vault deletion, receives a permanent whole-vault warning, and provides the exact confirmation phrase in a later turn. Permanently deletes every memory in the OAuth-selected vault. This cannot delete one memory; use delete_memories for specific items. Requires separate memories:delete authorization and destructive host confirmation.
- `consolidate_memories` — Use this when the user asks to consolidate, reflect on, or organize their memories, or when memory_status or a search result reports that consolidation is available. Checks out a batch of unconsolidated memories from the connected vault under a 15 minute lease and returns their texts plus server instructions for writing reflection entries. Follow the returned instructions to write the entries, the
- `commit_reflections` — Use this to complete a consolidation started with consolidate_memories. Submits the reflection entries you wrote for the checked-out batch. Each entry is standalone prose with an importance rating from 1 to 10. The server stores the reflections, links them to their source memories, and marks the sources consolidated. Safe to retry: committing the same batch twice returns the original result.
- `inspect_memory` — Use this when the user asks why the assistant believes something, or wants to see the source memories behind a reflection. Given a memory id from a search result, returns the lower-tier memories that reflection was built from, or, for a raw memory, which reflections it was consolidated into. Use repeatedly to drill down from a high-level reflection to the tier 2 reflections and raw memories beneat
- `delete_memories` — Use this only when the user explicitly asks to delete specific memories and confirms after seeing what will be deleted. Permanently deletes the identified memories from the connected vault by their ids from search or inspect results. Deleting a raw memory does not delete reflections built from it. This cannot be undone. For deleting everything, forget_all_memories is the separate whole-vault tool.
- `search` — Use this legacy compatibility alias when a client explicitly requests a tool named search. It searches the OAuth-selected MemoryRouter vault without modifying it. For normal ChatGPT recall, prefer search_memories; this tool does not provide citable item permalinks or Company Knowledge fetch support.

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