What is Roo Code Memory Bank Mcp Server

The roo-code-memory-bank-mcp-server is a Model Context Protocol (MCP) server that implements the core functionality of the Roo Code Memory Bank system, enabling AI assistants to maintain project context across sessions through interaction with a file-based memory bank using structured MCP tools.

Use cases

Use cases include managing project documentation, tracking decisions and progress over time, and providing AI assistants with a structured way to retrieve and update project-related information.

How to use

To use the roo-code-memory-bank-mcp-server, clone the repository, install the necessary dependencies using npm, and run the server in an MCP client environment. You can then utilize various tools provided by the server to manage memory bank entries.

Key features

Key features include initializing a memory bank with standard markdown files, checking the status of the memory bank, reading content from memory bank files, and appending new entries with timestamps under specific headers.

Where to use

The roo-code-memory-bank-mcp-server can be used in various fields such as software development, project management, and AI development, where maintaining context over multiple sessions is crucial.

Roo Code Memory Bank MCP Server

This project implements the core functionality of the Roo Code Memory Bank system as a Model Context Protocol (MCP) server. It allows AI assistants to maintain project context across sessions by interacting with a file-based memory bank using structured MCP tools.

Features

This MCP server provides the following tools:

• initialize_memory_bank: Creates the memory-bank/ directory and standard .md files (productContext.md, activeContext.md, progress.md, decisionLog.md, systemPatterns.md) with initial templates.
  • Input: (Optional) { "project_brief_content": string }
  • Output: { "status": "success" | "error", "messages"?: string[], "message"?: string }
• check_memory_bank_status: Checks if the memory-bank/ directory exists and lists the .md files within it.
  • Input: {}
  • Output: { "exists": boolean, "files": string[] }
• read_memory_bank_file: Reads the full content of a specified memory bank file.
  • Input: { "file_name": string }
  • Output: { "content": string } or error object.
• append_memory_bank_entry: Appends a new, timestamped entry to a specified file, optionally under a specific markdown header. Creates the file if it doesn’t exist.
  • Input: { "file_name": string, "entry": string, "section_header"?: string }
  • Output: { "status": "success" | "error", "message": string }

Prerequisites

• Node.js (v18 or later recommended)
• npm (usually included with Node.js)
• An MCP client environment (like the one used by Cline) capable of managing and launching MCP servers.

Installation

1. Clone the repository:

   git clone https://github.com/IncomeStreamSurfer/roo-code-memory-bank-mcp-server.git
   cd roo-code-memory-bank-mcp-server
   

2. Install dependencies:

   npm install
   

3. Build the project:

   npm run build
   

   This compiles the TypeScript code into JavaScript in the dist/ directory.

Configuration (for Cline MCP Client)

To make this server available to your AI assistant (like Cline), you need to add its configuration to your MCP settings file (e.g., cline_mcp_settings.json).

Find the mcpServers object in your settings file and add the following entry:

Important: Replace /path/to/your/cloned/repo/ with the correct absolute path to where you cloned the repository on your machine. Ensure the path separator is correct for your operating system (e.g., use backslashes \ on Windows).

Running the Server

You don’t typically need to run the server manually. The MCP client (like Cline) will automatically start the server using the command and args specified in the configuration file when one of its tools is called for the first time.

If you want to test it manually, you can run npm start from the project directory.

Usage

The AI assistant interacts with the server using the defined tools. The typical workflow involves:

1. Checking the memory bank status (check_memory_bank_status).
2. Initializing if needed (initialize_memory_bank).
3. Reading relevant files (read_memory_bank_file) to gain context.
4. Appending entries (append_memory_bank_entry) as decisions are made or progress occurs.

The memory-bank/ directory will be created in the same directory where the server process is started (which should be the root of this project directory when launched via the MCP client configuration).

Custom instructions

Set these instructions inside Roo

You must use MCPs where needed

I have a specific MCP flow:

Use context7 to find any relevant documentation pieces you will need for this process, ensure to feed any relevant knoweldege to any relevant subtasks - use context7 at all times to do research on important documentation if you’re unsure of something
Use google maps mcp in order to search for + - this will allow us to find the basic businesses we need to accomplish our task
Use brave search mcp to find URLs to scrape
Use fetch mcp with fetch_txt and fetch_markdown to find text and images on pages in order to convert into JSON files and create something in-depth
Use openrouter search to find general sentiment of topics, reviews, etc.

Utilize the roo-code-memory-bank-mcp server to maintain project context:

• At the start of a task or significant subtask, use check_memory_bank_status.
• If the memory bank exists (exists: true), use read_memory_bank_file for relevant files (e.g., productContext.md, activeContext.md) to load the current project context.
• Incorporate this loaded context into your planning and execution.
• When making significant decisions, progress updates, or architectural changes, use append_memory_bank_entry to record the information in the appropriate file (decisionLog.md, progress.md, etc.), ensuring context persistence.
• If the memory bank doesn’t exist, consider using initialize_memory_bank if appropriate for the project.