mcp-structured-memory
The mcp-structured-memory server is a Model Context Protocol (MCP) server that enables AI-assisted, structured memory management for focused projects using markdown files stored locally.
Core Capabilities:
Document Management: Create new structured memory documents, list all available documents, retrieve full documents or summaries, and search within documents
Content Organization: Update entire sections with Markdown formatting (append or replace), organize content into custom sections tailored to specific domains like travel planning or research
List Management: Add items to lists, update existing list items, and move items between sections within documents
AI Integration: Enable dynamic content updates through AI learning from conversations and automated organization
Data Protection: Automatically create timestamped backups before major updates to ensure data integrity
The server facilitates building and maintaining living documents for domain-specific applications, storing everything as standard markdown files in platform-specific local directories.
Supports storage of memory documents on Linux systems, with files stored in ~/.local/share/mcp-structured-memory/.
Supports storage of memory documents on macOS systems, with files stored in ~/Library/Application Support/mcp-structured-memory/.
Uses markdown files as the storage format for memory documents, allowing structured organization of information that can be easily read and updated.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-structured-memory create a new memory document for my research project on renewable energy"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
Related MCP server: CastPlan MCP
Typical usage
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.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.
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.
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-memoryOption 2: Install from source
git clone https://github.com/nmeierpolys/mcp-structured-memory.git
cd mcp-structured-memory
npm install
npm run buildConfiguration
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/
Available Tools
10 toolsadd_to_listC
Add an item to a list section in a memory document
Inputs: item (required), section (required), memory_id (required).
create_memoryA
Create a new structured memory document with optional initial content. IMPORTANT: After using this tool, you MUST show the user the complete installation instructions returned by the tool - the memory will not work without proper MCP server setup and project context configuration.
Inputs: name (required), content.
get_full_memoryA
Retrieve the complete content of a memory document with all Markdown formatting preserved (headings, bold, italic, code, links, tables, lists, etc.)
Inputs: memory_id (required).
get_memory_summaryC
Get a high-level summary of a memory document
Inputs: memory_id (required).
get_sectionC
Retrieve a specific section from a memory document
Inputs: section (required), memory_id (required).
list_memoriesB
List all available memory documents
Inputs: no named parameters.
move_list_itemC
Move an item from one section to another
Inputs: memory_id (required), to_section (required), from_section (required), item_identifier (required), +1 more.
search_within_memoryC
Search for information within a memory document
Inputs: query (required), memory_id (required).
update_list_itemC
Update an existing item in a list section
Inputs: section (required), updates (required), memory_id (required), item_identifier (required).
update_sectionC
Update an entire section of a memory document. Content supports full Markdown formatting including headings, bold, italic, code blocks, links, lists, tables, and all standard Markdown syntax.
Inputs: content (required), section (required), memory_id (required), mode.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 10 tools
Each tool has a clearly distinct purpose targeting specific operations on structured memory documents. For example, add_to_list, move_list_item, and update_list_item are all focused on list management but handle different actions (adding, moving, updating), while get_full_memory, get_memory_summary, and get_section provide different levels of retrieval detail. There is no ambiguity in tool selection.
All tools follow a consistent verb_noun naming pattern (e.g., create_memory, list_memories, update_section). The verbs are clear and descriptive, and there are no deviations in style or convention throughout the set, making it predictable and easy to understand.
With 10 tools, the count is well-scoped for managing structured memory documents. Each tool serves a specific function in the lifecycle (create, retrieve, update, search, list), and none feel redundant or unnecessary, fitting the domain appropriately without being overwhelming.
The tool set provides complete coverage for the structured memory domain, including creation (create_memory), listing (list_memories), retrieval at various levels (get_full_memory, get_memory_summary, get_section), updating (update_section, update_list_item), list management (add_to_list, move_list_item), and search (search_within_memory). There are no obvious gaps, and the tools support full CRUD and lifecycle operations.
Maintenance
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