Memory MCP

Name: Memory MCP
Author: yuvalsuede

by yuvalsuedeversion 1.2.1i★ –iRuns on your computer

Registry nameio.github.yuvalsuede/memory-mcp

Install

Overview

Description from the maker (original English)

Persistent memory + git snapshots for Claude Code. Never lose context or code.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "claude-code-memory"
      ]
    }
  }
}

Run this in your terminal

claude mcp add memory -- npx -y claude-code-memory

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "claude-code-memory"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "memory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "claude-code-memory"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account yuvalsuede, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7256 servers in this category
Published to the registry more recently than 2% of the other 7256 servers in this category
Basic checks equal to or better than 100% of the other 7256 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Memory MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.2.1) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

memory-mcp

Persistent memory + automatic git snapshots for Claude Code. Never lose context. Never lose code.

🧠 45 memories | 📊 2.8K tokens | 📸 23 snapshots | ⏱️ 5m ago

Why memory-mcp?

Problem	Solution
Re-explaining your project every session	Auto-captures decisions, patterns, architecture
Context window fills up, knowledge lost	Two-tier memory: CLAUDE.md (instant) + deep search
Broke something, can't remember what worked	Git snapshots on every save, instant rollback
No idea what Claude "knows" about your project	Visual dashboard shows all context
Worried about cloud storage	100% local files, your git repo

What makes it different

Git Snapshots — Every memory save commits your entire project. Roll back anytime.
Two-Tier Memory — CLAUDE.md loads instantly, deep store searchable mid-conversation.
LLM-Powered — Haiku extracts what matters, consolidates duplicates, prunes stale info.
Visual Dashboard — See your context: tokens, memories by type, snapshot history.
Zero friction — No commands to run. It just works silently.

Quick Start

# Install globally

npm install -g claude-code-memory

Interactive setup (API key + hooks)

memory-mcp setup

Initialize a project

memory-mcp init ~/Projects/my-app

That's it. Start coding. Memories accumulate automatically.

How It Works

graph TB

subgraph "Phase 1: Silent Capture" A[Claude Code Session] -->|User sends message| B[Claude responds] B -->|Hook fires: Stop/PreCompact/SessionEnd| C[extractor.js] C --> D[Read transcript from cursor] D --> E[Chunk if >6000 chars] E --> F[Send to Haiku LLM] F -->|Extract memories as JSON| G[Dedup via Jaccard similarity] G --> H[Save to .memory/state.json] H --> I[Decay confidence scores] I --> J{Consolidation needed?} J -->|>80 memories or every 10 extractions| K[Haiku merges/drops] J -->|No| L[Sync CLAUDE.md] K --> L end

subgraph "Phase 2: Recovery" M[New session starts] -->|Built-in behavior| N[Claude reads CLAUDE.md] N --> O[Claude has full project context] end

subgraph "Phase 3: Deep Recall" O --> P{Need specific context?} P -->|memory_search| Q[Keyword search across memories] P -->|memory_ask| R[Haiku synthesizes answer from top 30 matches] P -->|memory_related| S[Tag-based retrieval] end

style A fill:#4a9eff,color:#fff style F fill:#ff6b6b,color:#fff style K fill:#ff6b6b,color:#fff style R fill:#ff6b6b,color:#fff style T fill:#ffd93d,color:#000 style U fill:#6bcb77,color:#000

Two-tier memory architecture:

Layer	Purpose	Size
`CLAUDE.md`	Auto-read on session start. Top ~150 lines of the most important context.	Compact
`.memory/state.json`	Full memory store. Searchable via MCP tools mid-conversation.	Unlimited

Silent capture via hooks:

Claude Code hooks fire after every response (Stop), before context compaction (PreCompact), and at session end (SessionEnd). A fast LLM (Haiku) reads the transcript and extracts:

Architecture — how the system is structured
Decisions — why X was chosen over Y
Patterns — conventions and how things are done
Gotchas — non-obvious pitfalls
Progress — what's done, what's in flight
Context — business context, deadlines, preferences

Smart memory management:

Jaccard similarity deduplication (no duplicate memories)
Confidence decay (progress fades after 7 days, context after 30)
LLM-powered consolidation (merges overlapping memories, prunes stale ones)
Line-budgeted CLAUDE.md (stays under ~150 lines, most important first)

Updating

To update an existing installation:

npm install -g claude-code-memory --force

To update hooks (e.g., after a bug fix):

memory-mcp setup

Requirements

Claude Code CLI
Node.js 18+
Anthropic API key (for the Haiku-based extractor, ~$0.001 per extraction)

CLI Commands

memory-mcp setup              Interactive first-time setup

memory-mcp init [dir] Initialize memory for a project memory-mcp status [dir] Show memory status and health memory-mcp statusline [dir] Compact one-line status (great for shell prompts) memory-mcp context [dir] Show context metrics and token usage memory-mcp context --html Generate visual HTML dashboard memory-mcp search Search memories by keyword memory-mcp ask Ask a question, get answer from memory memory-mcp consolidate [dir] Merge duplicates, prune stale memories memory-mcp key [api-key] Set or check Anthropic API key memory-mcp snapshots [dir] List git snapshot history memory-mcp snapshot-enable Enable automatic git snapshots memory-mcp snapshot-disable Disable git snapshots memory-mcp help Show help

Context Dashboard

Visualize your memory usage with memory-mcp context:

Context Dashboard

Project: my-app

Total Context 2.8K estimated tokens

Tier 1 CLAUDE.md (auto-loaded) █████████████████░░░░░░░░░░░░░ 1.0K 45 lines, 44 in memory block

Tier 2 .memory/state.json (searchable) ██████████████████████████████ 1.8K 29 active, 5 archived, 24 superseded

Memories by Type architecture ███░░░░░░░░░░░░░░░░░ 8 memories (291 tokens) decision ██████░░░░░░░░░░░░░░ 18 memories (540 tokens) gotcha ████░░░░░░░░░░░░░░░░ 10 memories (332 tokens) progress ██████░░░░░░░░░░░░░░ 19 memories (538 tokens)

Git Snapshots ● Enabled on __memory-snapshots 42 commits → origin

Use memory-mcp context --html to generate an interactive browser dashboard.

Git Snapshots

Automatic project versioning tied to your working sessions. Every memory extraction commits your entire project to a hidden branch.

# Enable during init (you'll be prompted)

memory-mcp init ~/Projects/my-app

Or enable later

memory-mcp snapshot-enable

View snapshot history

memory-mcp snapshots

Compare two snapshots

memory-mcp snapshot-diff abc123 def456

Restore to a previous state

memory-mcp snapshot-restore abc123

Disable (preserves existing snapshots)

memory-mcp snapshot-disable

How it works:

Commits go to __memory-snapshots branch (invisible in normal workflow)
Optional push to remote (e.g., origin)
Commit messages include what memories were extracted
Full project state captured, not just memory files

Use cases:

Roll back after breaking changes
See what your project looked like during a specific session
Track project evolution alongside context evolution

MCP Tools (used by Claude mid-conversation)

When configured as an MCP server, Claude can access these tools during a session:

Tool	Description
`memory_search`	Keyword search across all memories
`memory_related`	Get memories by tag or area
`memory_ask`	Ask a question, get an LLM-synthesized answer from memory
`memory_save`	Manually save a memory
`memory_recall`	List all memories with filters
`memory_delete`	Remove a memory
`memory_consolidate`	Trigger memory consolidation
`memory_consciousness`	Generate the full consciousness document
`memory_stats`	Show memory statistics
`memory_init`	Set project name and description

What Gets Stored

Memories are categorized into six types:

architecture   "Next.js 14 app router with Supabase backend, Stripe for billing"

decision "Chose server components for public pages because of SEO requirements" pattern "All API routes validate input with zod and return NextResponse" gotcha "Supabase RLS policy on word_lists requires user_id OR org_id, not both" progress "Auth complete, billing webhook handling in progress" context "Client wants launch by March, focus on core features only"

File Structure

After initialization, your project gets:

your-project/

├── CLAUDE.md ← auto-updated memory summary (read on session start) ├── .memory/ │ ├── state.json ← full memory store │ └── cursor.json ← tracks what's been processed ├── .mcp.json ← MCP server configuration └── .claude/ └── settings.json ← hook configuration

CLAUDE.md Format

The memory block is inserted between markers, preserving any existing CLAUDE.md content:

<!-- MEMORY:START -->

MyProject

A brief description

_Last updated: 2026-01-27 | 45 active memories, 62 total_

Architecture

Next.js 14 app router with Supabase backend
Auth via NextAuth with Google and email providers

Key Decisions

Chose server components for SEO pages
Using Supabase RLS instead of API-level auth

Patterns & Conventions

All API routes use zod validation
Tailwind only, no CSS modules

Gotchas & Pitfalls

RLS policy requires user_id OR org_id, not both

Current Progress

Auth: complete
Billing: in progress

Context

Launch target: March

_For deeper context, use memory_search, memory_related, or memory_ask tools._

Global vs Per-Project Install

Global (recommended): hooks work for all projects automatically.

memory-mcp setup  # select "global" when prompted

Per-project: hooks and MCP configured per project.

memory-mcp init /path/to/project

Configuration

API key is resolved in order:

ANTHROPIC_API_KEY environment variable
~/.memory-mcp/config.json
~/.config/anthropic/api_key
~/.anthropic/api_key

Cost

The extractor uses Claude Haiku for memory extraction and consolidation. Typical cost:

~$0.001 per extraction (after each Claude response)
~$0.005 per consolidation (every ~10 extractions)
A full day of coding: ~$0.05–0.10

License

MIT

Memory MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

memory-mcp

Why memory-mcp?

What makes it different

Quick Start

Interactive setup (API key + hooks)

Initialize a project

How It Works

Updating

Requirements

CLI Commands

Context Dashboard

Git Snapshots

Or enable later

View snapshot history

Compare two snapshots

Restore to a previous state

Disable (preserves existing snapshots)

MCP Tools (used by Claude mid-conversation)

What Gets Stored

File Structure

CLAUDE.md Format

MyProject

Architecture

Key Decisions

Patterns & Conventions

Gotchas & Pitfalls

Current Progress

Context

Global vs Per-Project Install

Configuration

Cost

License