Provides cross-platform support with automatic path normalization for Linux systems when managing Memory Bank files
Provides cross-platform support with automatic path normalization for macOS systems when managing Memory Bank files
Maintains persistent project context through structured markdown files organized into five core categories for tracking project information
Offers integration through a published npm package for easy installation and configuration of the Memory Bank MCP
Incorporates Shields.io badges in the README for displaying language options and other metadata
Memory Bank MCP
A guided Memory Bank plugin for AI-assisted development
Memory Bank MCP is a Model Context Protocol (MCP) plugin that helps AI assistants maintain persistent project context through structured markdown files. It provides a systematic approach to tracking project goals, decisions, progress, and patterns through guided instructions rather than direct operations.
Features
Guided Operations: Provides instructions for AI assistants to perform operations themselves
Structured Context Management: Organize project information across 5 core files
Intelligent Guidance: Step-by-step instructions for initialization and updates
Flexible Updates: Smart update guidance based on different change types
Cross-Platform Support: Automatic path normalization for Windows/macOS/Linux
MCP Configuration
Using the published npm package:
Quick Start
Initialize Memory Bank
Use init-memory-bank to create the memory-bank directory and core filesRead Memory Bank
Use get-memory-bank-info to view all Memory Bank contentUpdate Memory Bank
Use update-memory-bank to get guidance on updating specific files
Core Files
1. productContext.md (Product Context)
High-level project overview
Goals and key features
Overall architecture
Automatically incorporates projectBrief.md if available
2. activeContext.md (Active Context)
Current work status
Recent changes
Open questions and issues
Focus areas
3. progress.md (Progress)
Task tracking in checklist format
Completed, current, and planned tasks
Progress timeline
4. decisionLog.md (Decision Log)
Architectural and implementation decisions
Rationale and implications
Decision history
5. systemPatterns.md (System Patterns)
Recurring patterns and standards
Coding conventions
Architectural patterns
Testing strategies
Usage Guidelines
For AI Assistants
Start Every Session: Check if memory-bank directory exists, then use
get-memory-bank-info
to understand project stateInitialize When Needed: Use
init-memory-bank
for new projectsRead Context: Use
get-memory-bank-info
to understand project stateUpdate Guidance: Use
update-memory-bank
to get update instructionsFollow Instructions: Execute the provided guidance to maintain Memory Bank
Update Triggers
Architecture Changes: Major structural decisions
Feature Completion: New features or capabilities
Bug Fixes: Significant issue resolutions
Refactoring: Code structure improvements
Decisions: Any important technical choices
Progress Updates: Task status changes
Tool Reference
init-memory-bank
Initializes Memory Bank with all core files.
Parameters:
rootPath
: Project root directory pathforce
(optional): Force re-initialization
Returns: Created files list and next steps guidance
get-memory-bank-info
Reads and returns all Memory Bank content (similar to codelf's get-project-info).
Parameters:
rootPath
: Project root directory path
Returns: Formatted Memory Bank content for AI context
update-memory-bank
Provides guidance for updating Memory Bank files.
Parameters:
rootPath
: Project root directory pathchangeType
: Type of change (architecture/feature/bugfix/refactor/decision/progress)description
: Brief description of the change
Returns: Detailed update instructions with templates and timestamps
Integration Tips
Cursor Setup
Add to Settings → Rules → User Rules:
Windsurf Setup
Add to Settings → Cascade → Memories and Rules → Global Rules:
Contributing
Contributions are welcome! Please feel free to submit issues or pull requests.
License
MIT
Acknowledgments
Inspired by the SPARC methodology and codelf.
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
A Model Context Protocol plugin that helps AI assistants maintain persistent project context through structured markdown files, providing a systematic approach to tracking project goals, decisions, progress, and patterns.
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