Memory Bank MCP

Memory Bank is an MCP server that helps teams create, manage, and access structured project documentation. It generates and maintains a set of interconnected Markdown documents that capture different aspects of project knowledge, from high-level goals to technical details and day-to-day progress.

Features

AI-Generated Documentation: Leverages Gemini API to automatically generate comprehensive project documentation
Structured Knowledge System: Maintains six core document types in a hierarchical structure
MCP Integration: Implements the Model Context Protocol for seamless integration with AI assistants
Customizable Location: Specify where you want your Memory Bank directory created
Document Templates: Pre-defined templates for project brief, product context, system patterns, etc.
AI-Assisted Updates: Update documents manually or regenerate them with AI assistance
Advanced Querying: Search across all documents with context-aware relevance ranking

Installation

# Clone the repository
git clone https://github.com/yourusername/memory-bank-mcp.git
cd memory-bank-mcp

# Install dependencies
npm install

# Create .env file with your Gemini API key (optional)
echo "GEMINI_API_KEY=your_api_key_here" > .env

Usage

Development Mode

# Start in development mode
npm run dev

Production Mode

# Build the project
npm run build

# Start in production mode
npm run start

MCP Configuration

To integrate Memory Bank with the Model Context Protocol (MCP), add the following configuration to your mcp.json file:

{
  "memoryBank": {
    "command": "node",
    "args": ["/path/to/memory-bank-mcp/dist/index.js"],
    "env": {
      "GEMINI_API_KEY": "your_gemini_api_key_here"
    }
  }
}

Replace /path/to/memory-bank-mcp/dist/index.js with the absolute path to your built index.js file, and add your Gemini API key (if applicable).

Example:

{
  "memoryBank": {
    "command": "node",
    "args": ["/Users/username/memory-bank-mcp/dist/index.js"],
    "env": {
      "GEMINI_API_KEY": "AIzaSyXXXXXXXXXXXXXXXXXXXXXXXX"
    }
  }
}

MCP Tools

Memory Bank MCP provides the following tools via the Model Context Protocol:

`initialize_memory_bank`

Creates a new Memory Bank structure with all document templates.

Parameters:

goal (string): Project goal description (min 10 characters)
geminiApiKey (string, optional): Gemini API key for document generation
location (string, optional): Absolute path where memory-bank folder will be created

Example:

await callTool({
  name: "initialize_memory_bank",
  arguments: {
    goal: "Building a self-documenting AI-powered software development assistant",
    location: "/Users/username/Documents/projects/ai-assistant"
  }
});

`update_document`

Updates a specific document in the Memory Bank.

Parameters:

documentType (enum): One of: projectbrief, productContext, systemPatterns, techContext, activeContext, progress
content (string, optional): New content for the document
regenerate (boolean, default: false): Whether to regenerate the document using AI

Example:

await callTool({
  name: "update_document",
  arguments: {
    documentType: "projectbrief",
    content: "# Project Brief\n\n## Purpose\nTo develop an advanced and user-friendly AI..."
  }
});

`query_memory_bank`

Searches across all documents with context-aware relevance ranking.

Parameters:

query (string): Search query (min 5 characters)

Example:

await callTool({
  name: "query_memory_bank",
  arguments: {
    query: "system architecture components"
  }
});

`export_memory_bank`

Exports all Memory Bank documents.

Parameters:

format (enum, default: "folder"): Export format, either "json" or "folder"
outputPath (string, optional): Custom output path for the export

Example:

await callTool({
  name: "export_memory_bank",
  arguments: {
    format: "json",
    outputPath: "/Users/username/Documents/exports"
  }
});

Document Types

Memory Bank organizes project knowledge into six core document types:

Project Brief (projectbrief.md): Core document defining project objectives, scope, and vision
Product Context (productContext.md): Documents product functionality from a user perspective
System Patterns (systemPatterns.md): Establishes system architecture and component relationships
Tech Context (techContext.md): Specifies technology stack and implementation details
Active Context (activeContext.md): Tracks current tasks, open issues, and development focus
Progress (progress.md): Documents completed work, milestones, and project history

License

MIT