How do I install Claude Memory Manager?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Claude Memory Manager need an API key?

No required environment variable is listed on this record.

What transport does Claude Memory Manager use?

Claude Memory Manager runs locally over stdio.

When was Claude Memory Manager last checked?

Last checked 2026-11-09. Cross-session memory for Claude Code — context capture, semantic search, recall

Claude Memory Manager MCP server

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Add to Cursor Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Local command

uvx claude-memory-manager==0.1.1

Claude Code has no install link for a local command. Copy the command below and run it in a terminal.

shClaude Code

1claude mcp add io.github.nyxtoolsdev-claude-memory-manager -- uvx claude-memory-manager==0.1.1

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.nyxtoolsdev-claude-memory-manager": {4      "command": "uvx",5      "args": [6        "claude-memory-manager==0.1.1"7      ]8    }9  }10}

claude_desktop_config.json

Local · pypiPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Version: 0.1.1
Last checked

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

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:

Parsing your Claude Code session logs (JSONL files)
Extracting meaningful memories with importance scoring
Embedding memories for semantic search
Storing everything in a local SQLite database with FTS5
Retrieving relevant context via hybrid semantic + keyword search
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)

MCP Setup

Claude Desktop

Find your Claude Desktop config file:
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
Add the memory server:

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

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):

Environment variables
Config file (~/.claude-memory/config.json)
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/

Claude Memory Manager

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Claude Memory Manager?

Does Claude Memory Manager need an API key?

What transport does Claude Memory Manager use?

When was Claude Memory Manager last checked?

Documentation

Claude Memory Manager

What It Does

Installation

Quick Start

1. Initialize the Database

2. Ingest Session Logs

3. Search Memories

4. Generate Context Summary

5. Connect to Claude Desktop (MCP)

CLI Reference

Global Options

Search Options

Categories

MCP Setup

Claude Desktop

MCP Tools

Architecture

Data Flow

Configuration

Environment Variables

Embedding Providers

FAQ

Development

License