LocalMem MCP

An easy-to-install MCP memory server that runs entirely on your machine with zero runtime dependencies. Stores memories, tasks, and a knowledge graph as plain, human-readable markdown files across chats. Syncable via iCloud, Dropbox, Syncthing or similar services.

Tools (19 total)

Memory

| Tool | Description | |------|-------------| | save_memory | Create a memory (title, content, category, tags, importance) | | read_memory | Read a memory - auto-increments access count | | list_memories | List memories sorted by score or creation date | | search_memories | Full-text search, results ranked by relevance score | | update_memory | Overwrite content, tags, or importance | | delete_memory | Delete a memory file | | get_context | Snapshot: top memories + active tasks + key entities |

Tasks

| Tool | Description | |------|-------------| | create_task | Create a task (title, description, priority, due, tags) | | list_tasks | List tasks, optionally filtered by status | | update_task | Update status, priority, due date, or content | | delete_task | Delete a task |

Knowledge Graph

| Tool | Description | |------|-------------| | create_entity | Create a named entity with type, observations, and importance | | get_entity | Retrieve an entity and all its relations | | list_entities | List entities sorted by importance, optionally filtered by type | | add_observation | Append an observation to an existing entity | | delete_entity | Delete an entity | | create_relation | Create a directed relation: source -[relation]-> target | | list_relations | List relations, optionally filtered by entity name | | delete_relation | Delete a relation by file path |

Installation

Option A - Download pre-built binary (easiest)

Go to the Releases page and download the archive for your platform:

| File | Platform | |------|----------| | localmem-macos-arm64.tar.gz | macOS Apple Silicon (M-Series) | | localmem-macos-amd64.tar.gz | macOS Intel | | localmem-windows-amd64.zip | Windows | | localmem-linux-amd64.tar.gz | Linux |

Extract it and place the binary anywhere on your machine. Note the full path, you will need it in the next step.

Option B - Build from source

1. Install Go

macOS (Homebrew):

brew install go

Windows (winget):

winget install GoLang.Go

Debian / Ubuntu:

sudo apt update && sudo apt install -y golang-go

2. Download LocalMem

Download the repository and open a terminal inside the folder.

3. Build the binary

go mod tidy
go build -o localmem .

This produces a single localmem binary in the current folder. No installer, no dependencies - just one file.

4. Connect to LM Studio

1. Open LM Studio
2. Go to Settings → MCP Servers
3. Add a new server entry:

{
  "mcpServers": {
    "localmem": {
      "command": "/home/user/localmem",
      "args": []
    }
  }
}

Replace /home/user/localmem with the actual path to the binary you built in step 3.

Tip: To find the full path, run pwd in the terminal where you built it, then append /localmem.

5. (Optional) Choose a memory folder

By default, LocalMem stores files in a memory/ folder next to the binary. To use a custom location - for example a synced folder for cross-device access - add a MEMORY_DIR environment variable:

{
  "mcpServers": {
    "localmem": {
      "command": "/home/user/localmem",
      "args": [],
      "env": {
        "MEMORY_DIR": "/home/user/localmem-memory"
      }
    }
  }
}

6. Verify it's working

Restart LM Studio. In a chat, ask the model to call get_context - it should return an empty context snapshot without errors. You're ready to go.

Other MCP clients

LocalMem works with any MCP-compatible client. The configuration format varies by client but always needs the path to the localmem binary and optionally MEMORY_DIR.

Cursor (~/.cursor/mcp.json):

{
  "mcpServers": {
    "localmem": {
      "command": "/home/user/localmem",
      "args": []
    }
  }
}

Claude Desktop (~/.config/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "localmem": {
      "command": "/home/user/localmem",
      "args": []
    }
  }
}

OpenWebUI: Go to Settings → Tools and add a new tool server pointing to the localmem binary.

Memory layout

memory/
├── general/            ← default category for memories
│   └── my-note.md
├── projects/
│   └── acme.md
├── tasks/              ← tasks & todos
│   └── buy-milk.md
├── entities/           ← knowledge graph nodes
│   └── alice.md
└── relations/          ← knowledge graph edges
    └── alice-works-at-acme.md

Relevance scoring

Each memory is scored as:

score = importance × log₂(access_count + 2) / (1 + 0.01 × days_since_access)

Memories decay slowly over time but recover each time they are read. High-importance memories (e.g. importance: 1.0) decay much more slowly than default ones.

Permanent memories

Memories tagged with any of the following tags are immune to decay and always return their raw importance score:

| Tag | Intended use | |-----|-------------| | permanent | General-purpose pin | | core | Fundamental facts that should always be available | | identity | Information about the user's identity or profile | | value | Personal values or principles | | principle | Rules or guidelines the model should always follow |

Example:

---
title: My name is Alex
tags: identity, permanent
importance: 1.0
---

The user's name is Alex. Always address them by name.

Cross-device sync

Set MEMORY_DIR to an iCloud Drive, Dropbox, or any synced folder to share memories across machines.

Credits

• mcp-go by mark3labs - Go SDK for the Model Context Protocol, used as the server transport layer.
• Model Context Protocol by Anthropic - the open protocol that lets language models communicate with external tools.
• Beledarian's mcp-local-memory - referenced for feature inspiration (knowledge graph, importance scoring, decay, tasks).
• MemPalace - inspiration for the fact-checking feature (similar name detection and relationship mismatch).
• Go - the programming language used to build the binary.