Memory Bank MCP Server

What is Memory Bank MCP Server?

Memory Bank MCP Server is a tool that helps build a structured documentation system based on Cline's Memory Bank pattern for context preservation in AI assistant environments. It integrates with AI code assistants like Cursor to create and manage project documentation.

How to use Memory Bank MCP Server?

Install via uvx, Smithery, Docker, or manually by cloning the repo and running the Python script. Configure the server in your mcp.json file, then ask your AI assistant to create a memory bank for your project.

Key features of Memory Bank MCP Server

• Get detailed information about Memory Bank structure
• Generate templates for Memory Bank files
• Analyze project summaries and provide suggestions

Use cases of Memory Bank MCP Server

• Create a memory bank for a new project to guide AI context
• Generate structured documentation files like project briefs or tech context
• Analyze a project summary to improve Memory Bank content
• Preserve context across AI assistant sessions

FAQ from Memory Bank MCP Server

What is the Memory Bank pattern?

It is a structured documentation system with core files (e.g., project brief, product context, active context) and optional context files, all in Markdown format, designed to preserve context in AI assistant environments.

How do I install Memory Bank MCP Server?

You can run it via uvx, Smithery, Docker, or manually by cloning the repository and running the Python virtual environment. Configuration is added to the MCP client's mcp.json file.

What tools does the server provide?

Three tools: get_memory_bank_structure (returns structure details), generate_memory_bank_template (returns a template for a specified file), and analyze_project_summary (analyzes a summary and provides suggestions).

What are the core Memory Bank files?

The required core files are: projectbrief.md, productContext.md, activeContext.md, systemPatterns.md, techContext.md, progress.md, and memory_bank_instructions.md.

Does the server require any special runtime?

Yes, it requires Python and can be run via uvx, Docker, or manually with a virtual environment. No special authentication or transport is mentioned.