Knowledge Graph Memory MCP server for AI agents

The Knowledge Graph Memory Server provides persistent memory capabilities for Claude using a local knowledge graph, allowing Claude to remember information about users across chat sessions. It organizes information through entities, relations, and observations to create a structured memory system.

Installation Options

VS Code Integration

You can configure the MCP server in VS Code using one of these methods:

Method 1: User Configuration (Recommended)

Open the Command Palette (Ctrl + Shift + P)
Run MCP: Open User Configuration
Add the server configuration to your mcp.json file:

Using NPX:

{
  "servers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ]
    }
  }
}

Using Docker:

{
  "servers": {
    "memory": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "-v",
        "claude-memory:/app/dist",
        "--rm",
        "mcp/memory"
      ]
    }
  }
}

Method 2: Workspace Configuration

Alternatively, create a file called .vscode/mcp.json in your workspace with the same configuration content as above.

Claude Desktop Configuration

Add this to your claude_desktop_config.json file:

Using Docker:

{
  "mcpServers": {
    "memory": {
      "command": "docker",
      "args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
    }
  }
}

Using NPX:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ]
    }
  }
}

Custom Configuration:

You can customize the server using environment variables:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ],
      "env": {
        "MEMORY_FILE_PATH": "/path/to/custom/memory.json"
      }
    }
  }
}

Available environment variables:

MEMORY_FILE_PATH: Path to the memory storage JSON file (default: memory.json in the server directory)

Using the Memory Server

Core Concepts

Entities

Entities are primary nodes in the knowledge graph with:

A unique name (identifier)
An entity type (e.g., "person", "organization")
A list of observations

Example:

{
  "name": "John_Smith",
  "entityType": "person",
  "observations": ["Speaks fluent Spanish"]
}

Relations

Relations define connections between entities:

{
  "from": "John_Smith",
  "to": "Anthropic",
  "relationType": "works_at"
}

Observations

Observations are discrete pieces of information about entities:

{
  "entityName": "John_Smith",
  "observations": [
    "Speaks fluent Spanish",
    "Graduated in 2019",
    "Prefers morning meetings"
  ]
}

Example System Prompt

Here's a sample prompt for using memory in chat personalization:

Follow these steps for each interaction:

1. User Identification:
   - You should assume that you are interacting with default_user
   - If you have not identified default_user, proactively try to do so.

2. Memory Retrieval:
   - Always begin your chat by saying only "Remembering..." and retrieve all relevant information from your knowledge graph
   - Always refer to your knowledge graph as your "memory"

3. Memory
   - While conversing with the user, be attentive to any new information that falls into these categories:
     a) Basic Identity (age, gender, location, job title, education level, etc.)
     b) Behaviors (interests, habits, etc.)
     c) Preferences (communication style, preferred language, etc.)
     d) Goals (goals, targets, aspirations, etc.)
     e) Relationships (personal and professional relationships up to 3 degrees of separation)

4. Memory Update:
   - If any new information was gathered during the interaction, update your memory as follows:
     a) Create entities for recurring organizations, people, and significant events
     b) Connect them to the current entities using relations
     c) Store facts about them as observations

API Tools

The server provides several tools for managing the knowledge graph:

create_entities

Creates multiple new entities in the knowledge graph.

create_relations

Creates new relationships between existing entities.

add_observations

Adds new observations to existing entities.

delete_entities

Removes entities and their associated relations.

delete_observations

Removes specific observations from entities.

delete_relations

Removes specific relations from the graph.

read_graph

Retrieves the entire knowledge graph structure.

search_nodes

Searches for nodes based on a text query.

open_nodes

Retrieves specific nodes by name.

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "memory" '{"command":"npx","args":["-y","@modelcontextprotocol/server-memory"]}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "memory": {
            "command": "npx",
            "args": [
                "-y",
                "@modelcontextprotocol/server-memory"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

{
    "mcpServers": {
        "memory": {
            "command": "npx",
            "args": [
                "-y",
                "@modelcontextprotocol/server-memory"
            ]
        }
    }
}

3. Restart Claude Desktop for the changes to take effect