io.github.yuvalsuede/memory-mcp MCP Server

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

    subgraph "Data Store"
        H -.-> T[(.memory/state.json<br/>Full memory store)]
        L -.-> U[(CLAUDE.md<br/>~150 line summary)]
        T -.->|MCP tools read| Q
        T -.->|MCP tools read| R
        T -.->|MCP tools read| S
    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 <query>      Search memories by keyword
memory-mcp ask <question>      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._
<!-- MEMORY:END -->

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:

1. ANTHROPIC_API_KEY environment variable
2. ~/.memory-mcp/config.json
3. ~/.config/anthropic/api_key
4. ~/.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