Memory MCP Server

By jcdiv47 GitHub

mcp-server-memory knowledge-graph

Overview

what is Memory MCP Server?

Memory MCP Server is a Python implementation of an MCP server designed to process and save memory in the form of a knowledge graph, enabling AI systems to store and recall information across sessions.

how to use Memory MCP Server?

To use the Memory MCP Server, install it via pip or uv, run the server, and configure it for your MCP clients by adding the necessary settings to your configuration files.

key features of Memory MCP Server?

Create and manage entities with structured information
Establish typed relations between entities
Add observations to existing entities
Delete entities, relations, and observations
Search nodes in the knowledge graph
Retrieve specific nodes by name

use cases of Memory MCP Server?

Maintaining a persistent knowledge graph for AI applications
Storing and retrieving structured data for machine learning models
Facilitating complex queries and data management in AI systems

FAQ from Memory MCP Server?

What programming language is Memory MCP Server written in?

Memory MCP Server is written in Python.

Is there a license for using Memory MCP Server?

Yes, it is licensed under the MIT License, allowing free use, modification, and distribution.

How can I customize the memory storage path?

You can customize the memory storage path using the MEMORY_FILE_PATH environment variable.

Content

Memory MCP Server

A Python implementation of an MCP server that processes and saves memory in the form of a knowledge graph.

Overview

MCP Server Memory provides functionality for maintaining a persistent knowledge graph for AI memory. It allows storing, retrieving, and querying structured data in the form of entities, relations, and observations. This enables AI systems to store and recall information across sessions.

Features

Create and manage entities with structured information
Establish typed relations between entities
Add observations to existing entities
Delete entities, relations, and observations
Search nodes in the knowledge graph
Retrieve specific nodes by name

Tools

The server implements the MCP (Model Control Protocol) interface, exposing the following tools:

create_entities: Create multiple new entities in the knowledge graph
create_relations: Create multiple new relations between entities
add_observations: Add new observations to existing entities
delete_entities: Delete entities and their associated relations
delete_observations: Delete specific observations from entities
delete_relations: Delete specific relations from the graph
read_graph: Read the entire knowledge graph
search_nodes: Search for nodes matching a query
open_nodes: Retrieve specific nodes by name

Installation

Using uv (recommended)

uv add mcp-server-memory

Using pip

pip install mcp-server-memory

Usage

Running the server

# Run the server directly
mcp-server-memory

# Set custom memory file path
MEMORY_FILE_PATH=/path/to/memory.json mcp-server-memory

Configuration

Configure for MCP clients

Add to your Claude(claude_desktop_config.json) or Cursor(mcp.json) settings file:

Using uv

"mcpServers": {
  "memory": {
    "command": "/path/to/uv",
    "args": [
      "--directory",
      "/path/to/mcp_server_memory/src",
      "run",
      "python",
      "-m",
      "mcp_server_memory"
    ],
    "env": {
      "MEMORY_FILE_PATH": "/path/to/memory.json"
    }
  }
}

Using pip installation

"mcpServers": {
  "memory": {
    "command": "python",
    "args": ["-m", "mcp_server_memory"]
  }
}

Configuring the Memory Path

By default, the knowledge graph data is stored in a memory.json file in the package directory. You can customize the location using the MEMORY_FILE_PATH environment variable.

Development

Clone the repository and install development dependencies:

git clone https://github.com/jcdiv47/mcp-server-memory.git
cd mcp-server-memory
uv venv
source .venv/bin/activate
uv install -e ".[dev]"

License

mcp-server-memory is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

No tools information available.