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Structured Memory

A Model Context Protocol server that automatically maintains structured, domain-specific memory documents for focused projects

42Fair

Scored 6 months ago · breakdown

About Structured Memory

Structured Memory is an MCP server in the Browser category: a Model Context Protocol server that automatically maintains structured, domain-specific memory documents for focused projects.

Install

Claude Code
claude mcp add structured-memory -- npx -y @nmeierpolys/mcp-structured-memory
npx
npx -y @nmeierpolys/mcp-structured-memory

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (10)

add_to_listAdd an item to a list section

Parameters not published.

create_memoryCreate a new memory document with optional initial content

Parameters not published.

get_full_memoryRetrieve the complete content of a memory document

Parameters not published.

get_memory_summaryGet a high-level summary of a memory document

Parameters not published.

get_sectionRetrieve a specific section from a memory document

Parameters not published.

list_memoriesList all available memory documents

Parameters not published.

move_list_itemMove an item between list sections

Parameters not published.

search_within_memorySearch for information within a memory document

Parameters not published.

update_list_itemUpdate an existing item in a list

Parameters not published.

update_sectionUpdate an entire section of a memory document

Parameters not published.

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README

Structured Memory MCP Server

A Model Context Protocol (MCP) server that provides structured, domain-specific memory management through markdown files. This is particularly useful for ongoing projects around a particular area of focus where you want to accumulate valuable context over time. Examples include focused domains like travel planning, research projects, real estate search, investment theses, product planning, and career development.

Why Structured Memory?

Traditional MCP memory servers use semantic search across scattered conversation snippets. This works well for general recall but fails for focused projects that need organized, categorical information.

Structured Memory instead maintains living documents with structured content that you can scan, update, and track over time - just like you would with a personal notebook, but with AI assistance.

Memory documents are stored as markdown files, primarily updated automatically by the LLM as it learns from your conversations to build rich context over time.

Typical usage

  1. Ask your LLM client to create a memory document for your focused project Create a new travel advisor memory document and tell me how to use it. This should start empty and grow over time.

  2. Create a new Project for conversations in that area. Add the provided usage instructions to your project context

    Note: LLMs will, against all tool advice, occasionally fail to show you the installation instructions. If that happens, follow up with a request to the LLM to show you the installation instructions and it should comply.

  3. New chat conversations start by checking the available info from the project's memory. Your LLM will update this memory over time to build up valuable context.

  4. Optionally prompt your LLM to add/adjust the memory file on demand. It's also helpful to ask the LLM to prompt you for relevant info (e.g. "Ask me some questions to learn about my travel preferences")

Installation

Option 1: Install from npm (when published)

npm install -g @nmeierpolys/mcp-structured-memory

Option 2: Install from source

git clone https://github.com/nmeierpolys/mcp-structured-memory.git
cd mcp-structured-memory
npm install
npm run build

Configuration

For Claude Desktop

Edit the claude_desktop_config.json file with the following entry:

{
  "mcpServers": {
    "mcp-structured-memory": {
      "command": "npx",
      "args": ["@nmeierpolys/mcp-structured-memory"]
    }
  }
}

Available Tools

  • create_memory - Create a new memory document with optional initial content
  • list_memories - List all available memory documents
  • get_memory_summary - Get a high-level summary of a memory document
  • get_section - Retrieve a specific section from a memory document
  • get_full_memory - Retrieve the complete content of a memory document
  • search_within_memory - Search for information within a memory document
  • update_section - Update an entire section of a memory document
  • add_to_list - Add an item to a list section
  • update_list_item - Update an existing item in a list
  • move_list_item - Move an item between list sections

Flexible Structure

Memory documents support any structure you need. The AI will help you organize sections based on your use case. Common examples:

  • Travel Planning: destinations, itinerary, accommodations, activities, restaurants, travel tips, budget tracker
  • Research Project: research questions, literature review, methodology, findings, data sources, next steps
  • Real Estate Search: search criteria, active listings, visited properties, rejected properties, market insights, agent contacts

Example: Automatic Memory Building

User: "Create a new Minnesota trip memory document and tell me how to use it. This should start empty and grow over time."

Claude: "I've created a travel memory document for your Minnesota trip. As we discuss your plans, I'll automatically update it with destinations, timing, preferences, and other details I learn about your trip."

User: "I want to see fall colors, go hiking, try local cuisine, and visit both the North Shore and the Twin Cities."

Claude: "I've noted your priorities in the memory: fall foliage viewing, hiking opportunities, local restaurants, North Shore destinations, and Twin Cities attractions. I'll keep track of specific recommendations as we explore options."

[Later conversation]
User: "What hiking trails have good fall colors?"

Claude: "Based on our previous discussions, I see you're focused on fall colors in Minnesota. Let me suggest some trails and I'll add the best ones to your travel memory..."

Backup and Version Control

The server automatically creates timestamped backups before major updates.

Storage Locations

Memory document files are stored as markdown files in:

  • macOS: ~/Library/Application Support/mcp-structured-memory/
  • Windows: %LOCALAPPDATA%\mcp-structured-memory\
  • Linux: ~/.local/share/mcp-structured-memory/

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Structured Memory

How do I install Structured Memory?

Run claude mcp add structured-memory -- npx -y @nmeierpolys/mcp-structured-memory, then add the server to your MCP client's configuration.

Is Structured Memory safe to use with an AI agent?

Its trust score is 42 out of 100 (fair). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Structured Memory still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.