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Memory Bank MCP Server

@tuncer-byte

Repository

Basic information

Category

Memory & Knowledge

Transports

stdio

Author

tuncer-byte

About Memory Bank MCP Server

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

Memory Bank MCP Server config

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

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

Memory Bank MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Memory Bank MCP?

Memory Bank MCP is an MCP server that helps teams create, manage, and access structured project documentation. It generates and maintains interconnected Markdown documents capturing all aspects of project knowledge, from high-level goals to technical details and daily progress. It is designed to be accessed by MCP-compatible clients and LLM agents.

How to use Memory Bank MCP?

Install via git clone and npm install. Configure with a Gemini API key via a .env file or the mcp.json configuration. Run in development mode with npm run dev or in production mode after npm run build && npm run start. Add the server to your MCP client’s mcp.json to expose its tools for initialization, document updates, querying, and export.

Key features of Memory Bank MCP

  • AI-generated documentation using the Gemini API
  • Structured knowledge system with six core document types
  • Implements the Model Context Protocol for LLM integration
  • Customizable storage location for the Memory Bank directory
  • Pre-defined templates for project brief, product context, and more
  • Advanced querying with context-aware relevance ranking

Use cases of Memory Bank MCP

  • Initialize a new project memory bank with all document templates
  • Update project documentation manually or regenerate it with AI
  • Search across all Memory Bank documents for relevant context
  • Export Memory Bank documents in JSON or folder format

Frequently asked questions

1

Is Memory Bank MCP a standalone application?

No, it is an MCP server—it is meant to be connected to MCP-compatible clients such as Claude Desktop or custom LLM agents, not run as a standalone app.

2

What runtime and environment does Memory Bank MCP require?

Node.js is required. Dependencies are installed via `npm install`. A Gemini API key is needed for AI-powered document generation and updates.

3

Where does Memory Bank MCP store project data?

Data is stored in a user-specified directory. The `location` parameter during initialization determines where the memory-bank folder is created.

4

What API key is needed for AI features?

A Gemini API key is required. It can be provided through a `.env` file or the `GEMINI_API_KEY` environment variable in the MCP client configuration.

5

How do I expose Memory Bank MCP tools to my client?

Add the server definition to your MCP client’s `mcp.json` file, specifying the command (`node`), the path to the built `index.js`, and optionally the Gemini API key. The server then exposes tools like `initialize_memory_bank`, `update_document`, `query_memory_bank`, and `export_memory_bank`.

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