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@lakehouse/memory-mcp

Persistent memory for AI assistants via Model Context Protocol (MCP).

Give your AI assistant a memory that persists across conversations. Works with Claude Code, Claude Desktop, Cursor, Windsurf, and any MCP-compatible client.

Features

  • Remember - Store facts, preferences, tasks, and context

  • Recall - Semantic search to find relevant memories

  • Forget - Remove outdated information

  • Two modes:

    • Lakehouse42 (recommended) - Full semantic search, deduplication, knowledge graph

    • Local - Simple file-based storage with keyword search

Related MCP server: engram

Quick Start

Claude Code

Add to ~/.claude/claude_code_config.json:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["@lakehouse/memory-mcp"]
    }
  }
}

That's it! Claude Code now has persistent memory using local storage.

For full semantic search capabilities, connect to Lakehouse42:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["@lakehouse/memory-mcp"],
      "env": {
        "LH42_URL": "https://api.lakehouse42.com",
        "LH42_API_KEY": "lh42_your_api_key"
      }
    }
  }
}

Get your API key at lakehouse42.com.

Claude Desktop

Add to Claude Desktop's config (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["@lakehouse/memory-mcp"],
      "env": {
        "LH42_URL": "https://api.lakehouse42.com",
        "LH42_API_KEY": "lh42_your_api_key"
      }
    }
  }
}

Cursor / Windsurf

Follow the same pattern - add the MCP server to your client's configuration.

Tools

remember

Store a memory for later recall.

Remember that the user prefers dark mode

Parameters:

  • content (required) - The information to remember

  • type - fact, preference, task, event, context, reflection

  • importance - 0.0 to 1.0 (default: 0.5)

recall

Search memories by semantic similarity.

What are the user's preferences?

Parameters:

  • query (required) - What to search for

  • limit - Max results (default: 5)

  • types - Filter by memory types

forget

Delete a memory by ID.

Parameters:

  • memoryId (required) - ID of memory to delete

  • reason - Reason for deletion

list_memories

List recent memories.

Parameters:

  • limit - Max results (default: 10)

memory_status

Check memory system status and backend info.

Local vs Lakehouse42

Feature

Local

Lakehouse42

Persistence

✅ JSON file

✅ Cloud

Search

Keyword matching

Semantic (AI-powered)

Deduplication

❌

✅ 3-tier

Knowledge graph

❌

✅ Entity relationships

History tracking

❌

✅ Full audit trail

Multi-device sync

❌

✅

Environment Variables

Variable

Description

LH42_URL

Lakehouse42 API URL (enables LH42 backend)

LH42_API_KEY

API key for authentication

DEBUG

Enable debug logging (true/false)

Programmatic Usage

import { createMemoryServer, LH42Backend } from "@lakehouse/memory-mcp";

// Create server with custom config
const server = await createMemoryServer({
  lh42Url: "https://api.lakehouse42.com",
  apiKey: "lh42_xxx",
  debug: true,
});

// Or use backends directly
const backend = new LH42Backend({
  url: "https://api.lakehouse42.com",
  apiKey: "lh42_xxx",
});

await backend.initialize();
await backend.remember({ content: "User likes TypeScript" });
const results = await backend.recall({ query: "programming preferences" });

Privacy

  • Local mode: All data stored in ~/.lakehouse42/memory-mcp/memories.json

  • Lakehouse42 mode: Data stored securely in your Lakehouse42 account

  • No data is sent to third parties

  • You control your memories

License

MIT

Available Tools

5 tools
forgetA

Delete a specific memory by ID. Use when information is outdated or incorrect.

Inputs: memoryId (required), reason.

list_memoriesB

List recent memories. Useful for reviewing what has been remembered.

Inputs: limit.

memory_statusA

Get status of the memory system including backend type and features available.

Inputs: no named parameters.

recallA

Search memories by semantic similarity. Returns the most relevant memories matching the query.

Inputs: query (required), limit, types.

rememberA

Store a memory for later recall. Use this to remember important facts, user preferences, decisions, or any information that should persist across conversations.

Inputs: content (required), type, importance.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.9/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct action: remember stores, recall searches, forget deletes, list_memories lists, and memory_status reports system status. There is no ambiguity or overlap between them.

    Naming Consistency4/5

    Names are mostly verb-based and readable, but there is a slight inconsistency: remember, recall, and forget are bare verbs, while list_memories is verb_noun and memory_status is noun_noun. A more uniform pattern like get_memory_status would improve consistency.

    Tool Count5/5

    With 5 tools, the server is well-scoped for a memory system. Each tool covers a necessary function without redundancy, making the set neither too thin nor overly heavy.

    Completeness4/5

    The tools cover the core CRUD operations (create, read, delete) plus status. The only minor gap is the lack of an explicit update tool, but users can forget and re-remember to modify entries, so the shortfall is easily worked around.

    Maintenance

    ActivityInactive
    ResponsivenessOutdated data

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