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  3. Memory MCP
Memory MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 2:50:16 PM

Memory MCP

User RatingsBe the first to rate and review this MCP server!
View Repository22 GitHub StarsTotal stargazers on GitHub for the source repository (22 stars).Visit Website
memorymongodbcontext-cachingllmconversation

MongoDB-backed MCP server for persistent memory storage, context caching, and relevance-based retrieval for LLM conversations.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for JamesANZ/memory-mcp, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This MCP server manages persistent memories and context window caching for AI conversations using MongoDB. It supports saving, retrieving, appending, and clearing memories with timestamps and LLM identification. It also archives conversation context intelligently, scores relevance, creates summaries, and enables tag-based searches. Use it to maintain long-term memory and context for multi-session AI interactions.

Use cases

β€’Persist conversation memories across sessions
β€’Archive and retrieve relevant conversation context
β€’Score and summarize archived content for context windows
β€’Search memories by tags for organized retrieval
β€’Manage long conversations with context caching

Key features

β€’Save, add, retrieve, and clear memories
β€’Archive and retrieve context with tags
β€’Relevance scoring of archived content
β€’Create conversation summaries
β€’MongoDB-backed persistent storage
β€’Automatic context archiving based on usage thresholds

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Memory MCP.

Extracted Tool Capabilities
Save, add, retrieve, and clear memories
Archive and retrieve context with tags
Relevance scoring of archived content
Create conversation summaries
MongoDB-backed persistent storage
Automatic context archiving based on usage thresholds

Documentation Overview

🧠 Memory MCP Server

Persistent memory and context window caching for LLM conversations. Save, retrieve, and manage memories with intelligent context archiving. MongoDB-backed storage.

An MCP (Model Context Protocol) server that provides memory management and context window caching for AI coding environments like Cursor and Claude Desktop.

Trust Score

Why Use Memory MCP?

  • πŸ’Ύ Persistent Storage – MongoDB-backed memory that survives sessions
  • 🧠 Context Caching – Intelligent archiving and retrieval of conversation context
  • 🏷️ Tag-based Search – Organize and find memories by tags
  • πŸ“Š Relevance Scoring – Automatically score archived content relevance
  • ⚑ Easy Setup – One-click install in Cursor or simple manual setup

Quick Start

Ready to add memory to your AI workflow? Install in seconds:

Install in Cursor (Recommended):

πŸ”— Install in Cursor

Or install manually:

Terminal
npm install -g @jamesanz/memory-mcp
# Or from source:
git clone https://github.com/JamesANZ/memory-mcp.git
cd memory-mcp && npm install && npm run build

Features

Basic Memory Tools

  • save-memories – Save memories to database (overwrites existing)
  • get-memories – Retrieve all stored memories
  • add-memories – Append new memories without overwriting
  • clear-memories – Remove all stored memories

Context Window Caching

  • archive-context – Archive conversation context with tags
  • retrieve-context – Retrieve relevant archived context
  • score-relevance – Score archived content relevance
  • create-summary – Create summaries of archived content
  • get-conversation-summaries – Get all summaries for a conversation
  • search-context-by-tags – Search archived content by tags

Installation

Cursor (One-Click)

Click the install link above or use:

Code
cursor://anysphere.cursor-deeplink/mcp/install?name=memory-mcp&config=eyJtZW1vcnktbWNwIjp7ImNvbW1hbmQiOiJucHgiLCJhcmdzIjpbIi15IiwiQGphbWVzYW56L21lbW9yeS1tY3AiXX19

Manual Installation

Requirements: Node.js 18+, npm, MongoDB

server.ts
# Clone and build
git clone https://github.com/JamesANZ/memory-mcp.git
cd memory-mcp
npm install
npm run build

# Set MongoDB connection string
export MONGODB_URI="mongodb://localhost:27017"

# Run server
npm start

Claude Desktop

Add to claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

config.json
{
  "mcpServers": {
    "memory-mcp": {
      "command": "node",
      "args": ["/absolute/path/to/memory-mcp/build/index.js"],
      "env": {
        "MONGODB_URI": "mongodb://localhost:27017"
      }
    }
  }
}

Restart Claude Desktop after configuration.

Configuration

Set the MongoDB connection string:

server.ts
export MONGODB_URI="mongodb://localhost:27017"

Default: mongodb://localhost:27017

Usage Examples

Save Memories

Store memories from a conversation:

config.json
{
  "tool": "save-memories",
  "arguments": {
    "memories": ["User prefers TypeScript", "User works on blockchain projects"],
    "llm": "claude",
    "userId": "user123"
  }
}

Retrieve Memories

Get all stored memories:

config.json
{
  "tool": "get-memories",
  "arguments": {}
}

Archive Context

Archive conversation context when it gets too long:

config.json
{
  "tool": "archive-context",
  "arguments": {
    "conversationId": "conv-123",
    "contextMessages": ["Message 1", "Message 2"],
    "tags": ["coding", "typescript"],
    "llm": "claude"
  }
}

Retrieve Relevant Context

Get archived content relevant to current conversation:

config.json
{
  "tool": "retrieve-context",
  "arguments": {
    "conversationId": "conv-123",
    "tags": ["coding"],
    "minRelevanceScore": 0.5,
    "limit": 10
  }
}

Context Window Caching

The system automatically:

  • Archives content when context usage reaches 80%
  • Retrieves relevant content when usage drops below 30%
  • Scores relevance using keyword overlap
  • Creates summaries to condense long conversations

Use Cases

  • Long Conversations – Manage context windows for extended sessions
  • Memory Persistence – Save important information across sessions
  • Context Retrieval – Bring back relevant past conversations
  • Research Projects – Organize and tag research conversations

Technical Details

Built with: Node.js, TypeScript, MCP SDK, MongoDB
Dependencies: @modelcontextprotocol/sdk, mongodb, zod
Platforms: macOS, Windows, Linux

Storage: MongoDB (default: mongodb://localhost:27017)

Contributing

⭐ If this project helps you, please star it on GitHub! ⭐

Contributions welcome! Please open an issue or submit a pull request.

License

ISC

Support

If you find this project useful, consider supporting it:

⚑ Lightning Network

Code
lnbc1pjhhsqepp5mjgwnvg0z53shm22hfe9us289lnaqkwv8rn2s0rtekg5vvj56xnqdqqcqzzsxqyz5vqsp5gu6vh9hyp94c7t3tkpqrp2r059t4vrw7ps78a4n0a2u52678c7yq9qyyssq7zcferywka50wcy75skjfrdrk930cuyx24rg55cwfuzxs49rc9c53mpz6zug5y2544pt8y9jflnq0ltlha26ed846jh0y7n4gm8jd3qqaautqa

β‚Ώ Bitcoin: bc1ptzvr93pn959xq4et6sqzpfnkk2args22ewv5u2th4ps7hshfaqrshe0xtp

Ξ Ethereum/EVM: 0x42ea529282DDE0AA87B42d9E83316eb23FE62c3f

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
22
Stargazers on the source repository.
Last commit
9mo ago
Most recent push to the default branch.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Memory MCP

It uses MongoDB to store and manage memories and archived context.

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Technical Specs & Signals

Category🧠Knowledge & Memory
PricingFree
More technical detailsExpand β–Ύ
AuthNo auth required
LicenseISC
ClientsCursor, Claude Desktop
Last updatedAug 9, 2026
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars22
GitHub Star CountTotal stargazers on GitHub representing community popularity (22 stars).
Last commit9mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Dec 10, 2025
43Quality signal: Fair Β· 43/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools19/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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