The Roo Code Memory Bank MCP Server helps maintain project context across sessions using file-based memory management. With this server, you can:
- Initialize a memory bank by creating a
memory-bank/
directory with standard markdown files - Check memory bank status and list existing files
- Read the full content of specific memory bank files
- Append timestamped entries to files, optionally under specific markdown headers, creating files if they don't exist
Manages a project memory bank using Markdown files, providing tools to initialize, read, and append to structured context files that maintain project knowledge across sessions.
Serves as the runtime environment for the memory bank system, allowing file operations to create, check, read, and update the contextual knowledge base.
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 thememory-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 }
- Input: (Optional)
check_memory_bank_status
: Checks if thememory-bank/
directory exists and lists the.md
files within it.- Input:
{}
- Output:
{ "exists": boolean, "files": string[] }
- Input:
read_memory_bank_file
: Reads the full content of a specified memory bank file.- Input:
{ "file_name": string }
- Output:
{ "content": string }
or error object.
- Input:
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 }
- Input:
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
- Clone the repository:
- Install dependencies:
- Build the project: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:
- Checking the memory bank status (
check_memory_bank_status
). - Initializing if needed (
initialize_memory_bank
). - Reading relevant files (
read_memory_bank_file
) to gain context. - 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
), useread_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.
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.
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