memory-mcp-server

memory-mcp-server

Gives any AI tool persistent, searchable memory across sessions using hybrid semantic and keyword search, running 100% locally with no API keys or cloud dependencies.

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Memory MCP Server

Universal personal memory system for AI assistants — a Model Context Protocol (MCP) server that gives any AI tool persistent, searchable memory across sessions.

Works with Claude Desktop, Cursor, Windsurf, Cline, Roo Code, OpenCode, Continue and any MCP-compatible client.

100% local. No API keys. No cloud. Your memories stay on your machine.


Features

  • Hybrid Search — semantic vector search + full-text keyword search, combined for best results
  • 100% Local — uses FastEmbed for embeddings, runs entirely on your machine
  • Zero Configuvx memory-mcp-server just works
  • Universal — one server, all your AI tools share the same memory
  • Structured — five memory types: preference, project, workflow, knowledge, summary
  • Auto-setup — one command to configure all your AI tools
  • Fast — SQLite + LanceDB, sub-second queries even with thousands of memories

Quick Start

Prerequisites

  • Python 3.11+
  • uv (recommended) or pip

Install

# Using uv (recommended)
uv tool install memory-mcp-server

# Or with pip
pip install memory-mcp-server

Auto-Configure All Your AI Tools

memory-mcp-setup setup

This detects your installed AI tools and adds memory-mcp to each one automatically.

Or Configure Manually

See Manual Configuration below.


Supported AI Tools

Tool Auto-Setup Manual Config
Claude Desktop
Cursor
Windsurf
Cline (VS Code)
Roo Code (VS Code)
OpenCode
Continue
Any MCP Client

Manual Configuration

Claude Desktop

Add to claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": ["memory-mcp-server"]
    }
  }
}

Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": ["memory-mcp-server"]
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": ["memory-mcp-server"]
    }
  }
}

Cline (VS Code)

Cline auto-detects MCP servers, or add manually in Cline MCP settings:

{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": ["memory-mcp-server"],
      "disabled": false,
      "autoApprove": []
    }
  }
}

Roo Code (VS Code)

Same format as Cline, in Roo MCP settings:

{
  "mcpServers": {
    "memory": {
      "command": "uvx",
      "args": ["memory-mcp-server"],
      "disabled": false,
      "autoApprove": []
    }
  }
}

OpenCode

Add to ~/.config/opencode/opencode.json:

{
  "mcp": {
    "memory": {
      "type": "local",
      "command": ["uvx", "memory-mcp-server"],
      "enabled": true
    }
  }
}

Any MCP Client (stdio transport)

uvx memory-mcp-server

The server communicates over stdio using the MCP protocol.


MCP Tools

The server exposes 6 tools:

Tool Description
memory_store Store a new memory with kind, tags, priority
memory_search Hybrid semantic + keyword search
memory_list List memories with optional filters
memory_update Update content, tags, or priority
memory_delete Delete a memory by ID
memory_stats Get total count and breakdown

Memory Kinds

Kind Use For
preference Personal preferences: coding style, tools, conventions
project Project-specific: architecture, tech stack, decisions
workflow Processes: PR flow, deployment steps, review checklists
knowledge Technical insights: gotchas, solutions, tips
summary Session summaries: key decisions, outcomes

Teaching Your AI to Use Memory

Copy the contents of SKILL.md into your AI tool's system prompt, custom instructions, or rules file. This teaches the AI when and how to use the memory tools.

Where to Put It

Tool Location
Claude Desktop Project Instructions or CLAUDE.md
Cursor .cursor/rules/*.mdc or Settings → Rules
Windsurf .windsurfrules
Cline .clinerules
Roo Code .roorules
OpenCode .opencode/skills/memory-system/SKILL.md
Continue .continue/rules/*.md

CLI Commands

# Auto-configure all detected AI tools
memory-mcp-setup setup

# Auto-configure a specific tool
memory-mcp-setup setup --tool cursor

# Preview config without writing (dry run)
memory-mcp-setup setup --dry-run

# Show config snippet for manual setup
memory-mcp-setup show-config --tool claude-desktop

# Health check
memory-mcp-setup doctor

Environment Variables

Variable Default Description
MEMORY_DATA_DIR Platform-specific (see below) Directory for memory database files
MEMORY_CACHE_DIR System default Cache directory for embedding model

Default Data Directory

Platform Path
macOS ~/Library/Application Support/memory-mcp/data
Linux ~/.local/share/memory-mcp/data
Windows %APPDATA%\memory-mcp\data

Architecture

┌─────────────────────────────────────────────┐
│              AI Tool (Client)                │
│  Claude / Cursor / Windsurf / Cline / ...    │
└────────────────┬────────────────────────────┘
                 │ MCP (stdio)
┌────────────────▼────────────────────────────┐
│          memory-mcp-server                   │
│                                              │
│  ┌─────────────┐  ┌──────────────────────┐  │
│  │   FastMCP    │  │   EmbeddingManager   │  │
│  │  (6 tools)   │  │  (FastEmbed/BGE)     │  │
│  └──────┬──────┘  └──────────┬───────────┘  │
│         │                    │               │
│  ┌──────▼────────────────────▼───────────┐  │
│  │           MemoryStore                  │  │
│  │                                        │  │
│  │  ┌──────────┐    ┌─────────────────┐  │  │
│  │  │  SQLite   │    │    LanceDB      │  │  │
│  │  │ metadata  │    │  vector index   │  │  │
│  │  │   + FTS   │    │  (384-dim BGE)  │  │  │
│  │  └──────────┘    └─────────────────┘  │  │
│  └────────────────────────────────────────┘  │
└──────────────────────────────────────────────┘
  • SQLite: stores memory metadata, supports full-text search via FTS5
  • LanceDB: stores embedding vectors, supports fast approximate nearest neighbor search
  • FastEmbed: runs BAAI/bge-small-en-v1.5 locally for 384-dimensional embeddings

Development

# Clone
git clone https://github.com/cmdparkour/memory-mcp-server.git
cd memory-mcp-server

# Install with dev dependencies
uv sync

# Run directly
uv run memory-mcp

# Run setup CLI
uv run memory-mcp-setup doctor

FAQ

Does it need an API key?

No. Everything runs locally — embedding model included.

Does it support Chinese / non-English languages?

Yes. The BGE embedding model supports multilingual text. SQLite FTS5 also handles CJK characters.

Can multiple AI tools share the same memory?

Yes — that's the whole point. All tools point to the same local database.

Where is my data stored?

See Default Data Directory. You can override with MEMORY_DATA_DIR.

How do I back up my memories?

Copy the data directory. It contains a SQLite database and a LanceDB folder.

How do I reset all memories?

Delete the data directory.


License

MIT — see LICENSE.

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