claude-memory-manager 0.1.1

Cross-session memory system for Claude Code — never lose context between sessions

Claude Memory Manager

Cross-session memory for Claude Code — never lose context between sessions.

Claude Memory Manager automatically captures architectural decisions, code changes, bug fixes, and configuration choices from your Claude Code sessions, then intelligently retrieves relevant context when you start new sessions.

What It Does

Every time you use Claude Code, valuable context is created and lost when the session ends:

• Which libraries you chose and why
• Bug fixes and their root causes
• Configuration decisions
• File structure and naming conventions
• Error resolutions

Claude Memory Manager solves this by:

1. Parsing your Claude Code session logs (JSONL files)
2. Extracting meaningful memories with importance scoring
3. Embedding memories for semantic search
4. Storing everything in a local SQLite database with FTS5
5. Retrieving relevant context via hybrid semantic + keyword search
6. Serving context to Claude Desktop via MCP protocol

Installation

pip install claude-memory-manager

For local embeddings (no API key needed):

pip install claude-memory-manager[local]

For development:

pip install claude-memory-manager[dev]

Quick Start

1. Initialize the Database

claude-memory init

This creates the SQLite database at ~/.claude-memory/memory.db and saves a config file.

2. Ingest Session Logs

# Ingest all sessions from the default path (~/.claude/projects/)
claude-memory ingest

# Ingest from a specific path
claude-memory ingest /path/to/sessions

# Watch for new sessions and auto-ingest
claude-memory ingest --watch

3. Search Memories

# Search across all memories
claude-memory search "authentication setup"

# Filter by project
claude-memory search "database schema" --project /path/to/project

# Filter by category
claude-memory search "cors" --category config

4. Generate Context Summary

# List all indexed projects
claude-memory context

# Generate summary for a specific project
claude-memory context /path/to/project

# With custom token limit
claude-memory context /path/to/project --max-tokens 3000

5. Connect to Claude Desktop (MCP)

Add to your Claude Desktop config (see MCP Setup):

{
  "mcpServers": {
    "claude-memory": {
      "command": "claude-memory-mcp",
      "args": []
    }
  }
}

CLI Reference

Command	Description
claude-memory init	Initialize the SQLite database
claude-memory ingest [PATH]	Ingest session logs from path
claude-memory ingest --watch	Watch and auto-ingest new sessions
claude-memory search "query"	Hybrid semantic + keyword search
claude-memory context [PROJECT]	Generate context summary
claude-memory list	List all indexed sessions
claude-memory stats	Database statistics
claude-memory prune --older-than 90d	Remove old memories
claude-memory export	Export memories as JSON
claude-memory serve	Start MCP server mode

Global Options

Option	Description
--config PATH	Custom config file path
--verbose / -v	Enable debug logging
--version	Show version

Search Options

Option	Description
--project / -p	Filter by project path
--category / -c	Filter by category
--limit / -n	Max results (default: 5)

Categories

Memories are classified into these categories:

• decision — Architectural and design decisions
• code_change — Significant code modifications
• bug_fix — Bug identification and resolution
• config — Configuration and environment changes
• error_resolution — Errors encountered and solved
• preference — User preferences and conventions
• discussion — General discussion summaries

MCP Setup

Claude Desktop

1. Find your Claude Desktop config file:

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

2. Add the memory server:

{
  "mcpServers": {
    "claude-memory": {
      "command": "claude-memory-mcp",
      "args": []
    }
  }
}

3. Restart Claude Desktop.

See examples/claude-desktop-config.json for a complete example.

MCP Tools

Once connected, Claude Desktop can use these tools:

Tool	Description
memory_search	Search memories by query with optional filters
memory_recall	Get a formatted context summary for a project
memory_save	Save a new memory directly
memory_stats	Get database statistics

Architecture

claude-memory-manager/
  src/claude_memory/
    cli.py              # Click CLI commands
    mcp_server.py       # MCP stdio server
    config.py           # Configuration management
    core/
      extractor.py      # Memory extraction from conversations
      embedder.py       # Embedding generation + caching
      indexer.py         # Pipeline: parse -> extract -> embed -> store
      retriever.py      # Hybrid semantic + keyword search
      summarizer.py     # Context summary generation
    parsers/
      jsonl_parser.py   # Claude Code session log parser
      diff_parser.py    # Unified diff parser
    storage/
      database.py       # SQLite + FTS5 operations
      models.py         # Pydantic data models
      migrations.py     # Schema versioning
    integrations/
      anthropic_embeddings.py  # Voyage AI API
      local_embeddings.py      # sentence-transformers
    utils/
      formatting.py     # CLI output formatting
      license.py        # License validation

Data Flow

Session Logs (.jsonl)
        |
  [JSONL Parser] -----> ParsedSession
        |
  [Extractor] --------> Memory objects (categorized, scored)
        |
  [Embedder] ----------> Embeddings (bytes for SQLite BLOB)
        |
  [Indexer] -----------> SQLite DB (with FTS5 index)
        |
  [Retriever] ---------> Search results (hybrid ranked)
        |
  [Summarizer] --------> Context summary (markdown)

Configuration

Configuration is loaded from (in priority order):

1. Environment variables
2. Config file (~/.claude-memory/config.json)
3. Defaults

Environment Variables

Variable	Description	Default
CLAUDE_SESSIONS_PATH	Path to session logs	~/.claude/projects
CLAUDE_MEMORY_DB_PATH	Database file path	~/.claude-memory/memory.db
CLAUDE_MEMORY_EMBEDDING_PROVIDER	anthropic, voyage, or local	local
ANTHROPIC_API_KEY	Anthropic API key	—
VOYAGE_API_KEY	Voyage AI API key	—
CLAUDE_MEMORY_MAX_TOKENS	Max tokens for context	2000
CLAUDE_MEMORY_LOG_LEVEL	Log level	INFO

Embedding Providers

Provider	Dimension	Requires
voyage	1024	VOYAGE_API_KEY
anthropic	1024	ANTHROPIC_API_KEY
local	384	pip install claude-memory-manager[local]

If no provider is available, a stub provider is used (keyword search still works, but semantic search is disabled).

FAQ

Where are my memories stored? In a SQLite database at ~/.claude-memory/memory.db. All data stays local.

Does this send my code to any API? Only if you configure the Voyage or Anthropic embedding provider. In that case, only memory text content (not full session logs) is sent to generate embeddings. Use local for fully offline operation.

How does deduplication work? Each memory's content is hashed (SHA-256). If a memory with the same hash already exists, it is skipped during ingestion.

How does hybrid search work? Results from cosine-similarity vector search (70% weight) are combined with SQLite FTS5 keyword search results (30% weight). Memories appearing in both get combined scores.

Can I export my memories? Yes: claude-memory export > memories.json or claude-memory export -o file.json.

How do I prune old memories? claude-memory prune --older-than 90d removes memories older than 90 days. Supports d (days), w (weeks), m (months), y (years).

Development

# Clone and install in development mode
git clone https://github.com/nyxtools/claude-memory-manager.git
cd claude-memory-manager
pip install -e ".[dev]"

# Run tests
pytest

# Type check
mypy src/

# Lint
ruff check src/ tests/

License

MIT License. Copyright (c) 2026 NyxTools · LEW Enterprises LLC.