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Memento

Persistent memory system for LLMs with lossless transcript management. Designed for Claude via Claude Code.

Memento operates as an engine-lite: a two-layer memory system that captures everything and forgets nothing. The knowledge layer stores distilled facts, decisions, and preferences. The transcript layer stores full session history with a hierarchical summary DAG, enabling regex search and lossless drill-down across all past conversations.

Inspired by the Lossless Context Management (LCM) architecture.

How It Works

Session Start ──> inject core memories + recent session summaries
                  (if resuming after compaction: inject recovery context)
                       │
                       ▼
  ┌──────────── TURN LOOP ─────────────┐
  │ UserPromptSubmit ──> persist user    │
  │ PostToolUse ────────> persist tools  │
  │ Stop ───────────────> persist reply  │
  └──────────────────────────────────────┘
                       │
              [context fills up]
                       │
  PreCompact ──> generate checkpoint summary ──> inject as context
  PostCompact ─> capture Claude's compact_summary
  SessionStart(compact) ──> inject rich recovery context
                       │
  Session End ──> batch ingest full transcript
                  extract knowledge memories
                  detect file artifacts
                  link related sessions
                  build summary DAG (async)

Related MCP server: BuildAutomata Memory MCP Server

Architecture

┌──────────────────────────────────────────────────────────────┐
│                    MCP Tools (7)                              │
│  recall · remember · transcript_grep · transcript_expand     │
│  transcript_describe · llm_map                               │
└──────────────────────────┬───────────────────────────────────┘
                           │
┌──────────────────────────▼───────────────────────────────────┐
│  Knowledge Layer                                             │
│  memories + edges + dedup + merge + diversify                │
├──────────────────────────────────────────────────────────────┤
│  Transcript Layer                                            │
│  sessions + messages + FTS5 + summary DAG + artifacts        │
├──────────────────────────────────────────────────────────────┤
│  Engine-Lite (hooks)                                         │
│  real-time ingest + compaction awareness + context recovery   │
└──────────────────────────────────┬──────────────────────────┘
                              ┌────▼────┐
                              │ SQLite  │
                              │  + vec  │
                              └─────────┘

Storage: SQLite (WAL mode) with sqlite-vec for HNSW vector search and FTS5 for full-text search. Single file per project, zero infrastructure.

Embeddings: Ollama with nomic-embed-text (768-dim). Zero external API calls.

Summarization: Ollama with qwen2.5:3b for summaries and extraction. Three-level escalation guarantees convergence (LLM -> bullet points -> deterministic truncate).

Requirements

  • macOS (Apple Silicon recommended) or Linux

  • Node.js 20+

  • Docker (only for Ollama, or install Ollama natively)

Quick Start

git clone https://github.com/diego-ninja/memento.git
cd memento

# Install deps + start Ollama + build + pull models
make setup

# Start Ollama
make start

# Verify
make status
make test

Infrastructure

Component

Type

Purpose

SQLite

Embedded

All storage (memories, transcripts, vectors, FTS)

sqlite-vec

Extension

HNSW vector search

Ollama

Docker/Native

Embeddings + summarization (local LLM)

Ollama runs as a Docker container on port 11435 by default. Alternatively, install Ollama natively and point MEMENTO_OLLAMA_HOST to it.

Configure Claude Code

1. MCP Server

Add to your project's .claude/settings.json:

{
  "mcpServers": {
    "memento": {
      "command": "node",
      "args": ["dist/server.js"],
      "cwd": "/path/to/memento"
    }
  }
}

2. Hooks

Add to your global ~/.claude/settings.json:

{
  "hooks": {
    "SessionStart": [
      { "matcher": "startup", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/session-start.sh", "timeout": 10 }] },
      { "matcher": "compact", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/session-start.sh", "timeout": 10 }] }
    ],
    "UserPromptSubmit": [
      { "matcher": ".*", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/user-prompt.sh", "timeout": 3 }] }
    ],
    "Stop": [
      { "matcher": ".*", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/stop.sh", "timeout": 3 }] }
    ],
    "PostToolUse": [
      { "matcher": ".*", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/post-tool.sh", "timeout": 3 }] }
    ],
    "PreCompact": [
      { "matcher": ".*", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/pre-compact.sh", "timeout": 15 }] }
    ],
    "PostCompact": [
      { "matcher": ".*", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/post-compact.sh", "timeout": 5 }] }
    ],
    "SessionEnd": [
      { "matcher": ".*", "hooks": [{ "type": "command", "command": "/path/to/memento/hooks/session-end.sh", "timeout": 30 }] }
    ]
  }
}

3. CLAUDE.md instructions

Add to your global ~/.claude/CLAUDE.md:

# Memento -- Persistent Memory

You have access to a persistent memory system via MCP (memento).
Use it transparently -- the user should NOT notice you are consulting
or storing memories.

## When to recall (automatic)

- Starting a new session (hooks load context, but recall for specific topics)
- Before architectural or design decisions
- When the user references something "we discussed" or "last time"
- Unsure about a user preference

## When to remember

Call remember() immediately after:
- Completing a brainstorming or design session
- Writing or validating a design document
- User approving a plan
- Solving a complex bug with reusable learnings

## Transcript tools

- transcript_grep(pattern) — search full session history across all sessions
- transcript_expand(id) — drill into any summary to see original messages
- transcript_describe(id) — quick metadata for sessions, summaries, artifacts

MCP Tools

Knowledge Layer

Tool

Description

recall

Hybrid text+vector search over distilled memories. Returns top-3 with graph-based diversity.

remember

Store memories with automatic dedup (>0.92 skip), merge (0.80-0.92), and graph edge creation.

Transcript Layer

Tool

Description

transcript_grep

Substring/FTS5 search across all past session transcripts. Filter by session, role, limit.

transcript_expand

Lossless drill-down: summary ID, session ID, or message ID -> original messages with context.

transcript_describe

Metadata inspection for sessions (with artifacts, linked sessions), summaries, messages.

Operators

Tool

Description

llm_map

Process N items in parallel with a prompt template. Configurable concurrency and retries.

Hooks

Hook

Event

Purpose

session-start.sh

SessionStart (startup/compact)

Inject core memories + session summaries. Post-compact: inject recovery context.

user-prompt.sh

UserPromptSubmit

Real-time capture of user prompts to immutable store.

stop.sh

Stop

Real-time capture of assistant responses.

post-tool.sh

PostToolUse

Real-time capture of tool calls (Read, Write, Bash, etc).

pre-compact.sh

PreCompact

Generate checkpoint summary and inject as additionalContext (survives compaction).

post-compact.sh

PostCompact

Capture Claude Code's compact_summary into the summary DAG.

subagent-stop.sh

SubagentStop

Ingest sub-agent transcripts + persist final message in parent session.

session-end.sh

SessionEnd

Batch ingest transcript + extract memories + detect artifacts + link sessions + build DAG.

Data Storage

~/.memento/
├── config.json                  # Optional config overrides
└── projects/
    └── {sha256-hash}/
        ├── memories.db          # Knowledge layer (memories + edges + vector index)
        └── transcripts.db       # Transcript layer (sessions, messages, summaries, artifacts)

Knowledge Layer (memories.db)

Table

Purpose

memories

Distilled knowledge: decisions, learnings, preferences, facts

memories_fts

FTS5 full-text search index

vec_memories

sqlite-vec HNSW vector index (768-dim embeddings)

memory_edges

Semantic graph: bidirectional edges between related memories

Transcript Layer (transcripts.db)

Table

Purpose

sessions

Session metadata with root summary pointer

messages

Immutable verbatim transcript (every message, every turn)

messages_fts

FTS5 virtual table for full-text search

summaries

Hierarchical DAG nodes (leaf, condensed, compact_capture)

summary_sources

DAG edges: summary -> messages/summaries (provenance)

artifacts

Tracked file references with exploration summaries

session_edges

Cross-session links (continuation, related)

Memory Types

Type

Purpose

decision

Architectural or design choices

learning

Bugs resolved, patterns discovered

preference

User preferences expressed or inferred

context

Session summaries, work context

fact

Non-obvious codebase facts

CLI Commands

Knowledge

Command

Description

recall <query>

Search memories

stats

Show memory count

core

List core memories

maintain

Degrade stale core memories (>30 days)

extract <transcript>

Extract memories from a transcript file

flush

Delete all memories

Transcript

Command

Description

sessions --recent N

List recent sessions with summaries

ingest-message --session <id> --role <role> --content <text>

Persist a single message (used by hooks)

ingest-transcript --session <id> --path <file>

Batch ingest a full JSONL transcript

build-dag --session <id>

Build hierarchical summary DAG

checkpoint --session <id>

Generate session checkpoint for pre-compact

session-summary --session <id>

Get root summary of a session

store-compact-summary --session <id> --summary <text>

Store Claude's compact_summary

detect-artifacts --session <id>

Find and store file artifacts

link-sessions

Create edges between related sessions

Project Structure

src/
├── server.ts                   # MCP server entry point (7 tools)
├── cli.ts                      # CLI for hooks and manual use
├── config.ts                   # Configuration + project paths
├── types.ts                    # Core type definitions
├── extract.ts                  # Transcript extraction (LLM + regex)
├── tools/
│   ├── recall.ts               # Knowledge recall with graph boost + diversify
│   ├── remember.ts             # Knowledge store with dedup pipeline
│   ├── transcript-grep.ts      # Regex/FTS search over transcripts
│   ├── transcript-expand.ts    # Lossless summary -> message drill-down
│   ├── transcript-describe.ts  # Metadata inspection
│   └── llm-map.ts              # Parallel batch processing operator
├── transcript/
│   ├── db.ts                   # TranscriptDb (SQLite: sessions, messages, summaries, artifacts, edges)
│   ├── parse.ts                # Claude Code JSONL transcript parser
│   ├── ingest.ts               # Single message + batch transcript ingestion
│   ├── summarize.ts            # Three-level escalation + DAG construction
│   ├── artifacts.ts            # File artifact detection + exploration summaries
│   ├── session-edges.ts        # Cross-session edge detection
│   └── tokens.ts               # Token estimator
├── storage/
│   ├── unified.ts              # UnifiedStorage (SQLite + sqlite-vec + FTS5)
│   └── pipeline.ts             # Shared dedup/merge pipeline
├── search/
│   ├── hybrid.ts               # Hybrid text+vector search (RRF fusion)
│   └── reranker.ts             # Recency + type weight + graph degree ranking
└── embeddings/
    └── ollama.ts               # Ollama client (embeddings + merge + summarize)

hooks/
├── session-start.sh            # Startup + post-compact recovery
├── user-prompt.sh              # Real-time user prompt capture
├── stop.sh                     # Real-time assistant response capture
├── post-tool.sh                # Real-time tool call capture
├── pre-compact.sh              # Checkpoint summary injection
├── post-compact.sh             # Compact summary capture
└── session-end.sh              # Final ingest + extract + DAG + artifacts + edges

Configuration

Default config (override via ~/.memento/config.json):

{
  "ollama": {
    "host": "http://127.0.0.1:11435",
    "embeddingModel": "nomic-embed-text",
    "generativeModel": "qwen2.5:3b"
  },
  "search": {
    "topK": 20,
    "finalK": 3,
    "deduplicationThreshold": 0.92,
    "mergeThreshold": 0.80,
    "rrfK": 60
  },
  "core": {
    "promoteAfterRecalls": 3,
    "degradeAfterSessions": 30
  }
}

License

MIT

A
license - permissive license
-
quality - not tested
D
maintenance

Maintenance

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