Mcp Knowledge Graph

Name: Mcp Knowledge Graph
Author: shaneholloman

@shaneholloman

Repository

About Mcp Knowledge Graph

MCP server enabling persistent memory for Claude through a local knowledge graph - fork focused on local development

#typescript #mcp #knowledge-graph #claude-ai #ai-memory #memory-server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "Aim-Memory-Bank": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-knowledge-graph",
        "--memory-path",
        "/Users/yourusername/.aim"
      ]
    }
  }
}

Tools

Store new memories (people, projects, concepts)

Add facts to existing memories

Link two memories together

Search memories by keyword

Retrieve specific memories by exact name

Read all memories in a database

List available databases

Forget memories

Remove specific facts from a memory

Remove links between memories

Overview

What is Mcp Knowledge Graph?

Mcp Knowledge Graph is an MCP server that gives AI models persistent memory through a local knowledge graph. It stores and retrieves information across conversations using entities, relations, and observations, and works with Claude Code/Desktop and any MCP‑compatible AI platform.

How to use Mcp Knowledge Graph?

Add the server to your claude_desktop_config.json or .claude.json using npx -y mcp-knowledge-graph --memory-path <path>. Optionally create a .aim directory in a project for project‑local storage. Once configured, the AI can use tools prefixed with aim_ (e.g., aim_memory_store, aim_memory_search) to manage memories.

Key features of Mcp Knowledge Graph

Master Database used by default for all operations
Multiple named databases for organizing memories by topic
Automatic project‑local memory using .aim directories
Location override to force project or global storage
Safe operations with built‑in file marker protection
Database discovery to list all available stores

Use cases of Mcp Knowledge Graph

Remembering user preferences, project details, or personal information across AI conversations
Organizing memories into separate databases (work, personal, health) by context
Keeping memory files in a synced folder (e.g., Dropbox) for access across multiple machines
Project‑local memory that stays within a codebase, with automatic detection via .aim directory

FAQ from Mcp Knowledge Graph

What are the `.aim` directory and `_aim` file marker?

The .aim directory is a project‑local folder that triggers automatic memory storage. The _aim marker is a safety line ({"type":"_aim","source":"mcp-knowledge-graph"}) placed at the start of every memory file to prevent accidental overwrites of unrelated JSONL files.

How does storage location work?

If a .aim directory exists in the current project, memory files are stored there. Otherwise, the configured global --memory-path directory is used. You can also force project or global location with an optional location parameter.

How do I use multiple named databases?

Pass a context parameter (e.g., "work", "personal") to memory tools. The system automatically creates new database files (e.g., memory-work.jsonl) alongside the master memory.jsonl. No manual setup is required.

What happens if a file lacks the `_aim` marker?

The server refuses to write to the file and returns an error: “File does not contain required _aim safety marker”. Either add the marker manually or delete the file and let the system recreate it.

What are the requirements to run this server?

Node.js version 22 or later and an MCP‑compatible AI platform (e.g., Claude Desktop).

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