Fork notice: This is a fork of thedotmack/claude-mem that adds custom AI provider support (any OpenAI-compatible API as the LLM backend — see Custom Provider Configuration). It is published on npm as @min202299/claude-mem, so the install commands below use that scoped package name.

Quick Start

Install with a single command:

npx @min202299/claude-mem install

Or install for Gemini CLI (auto-detects ~/.gemini):

npx @min202299/claude-mem install --ide gemini-cli

Or install for OpenCode:

npx @min202299/claude-mem install --ide opencode

Or install from the plugin marketplace inside Claude Code:

/plugin marketplace add MIN202299/claude-mem

/plugin install claude-mem

Restart Claude Code or Gemini CLI. Context from previous sessions will automatically appear in new sessions.

Note: The package is also importable as an SDK/library, but npm install -g @min202299/claude-mem installs the SDK/library only — it does not register the plugin hooks or set up the worker service. Always install via npx @min202299/claude-mem install or the /plugin commands above.

Once installed, the CLI command itself is still claude-mem (e.g. npx @min202299/claude-mem start, npx @min202299/claude-mem status).

🦞 OpenClaw Gateway

Install claude-mem as a persistent memory plugin on OpenClaw gateways with a single command:

curl -fsSL https://install.cmem.ai/openclaw.sh | bash

The installer handles dependencies, plugin setup, AI provider configuration, worker startup, and optional real-time observation feeds to Telegram, Discord, Slack, and more. See the OpenClaw Integration Guide for details.

Key Features:

• 🧠 Persistent Memory - Context survives across sessions
• 📊 Progressive Disclosure - Layered memory retrieval with token cost visibility
• 🔍 Skill-Based Search - Query your project history with mem-search skill
• 🖥️ Web Viewer UI - Real-time memory stream at http://localhost:37777
• 💻 Claude Desktop Skill - Search memory from Claude Desktop conversations
• 🔒 Privacy Control - Use <private> tags to exclude sensitive content from storage
• ⚙️ Context Configuration - Fine-grained control over what context gets injected
• 🤖 Automatic Operation - No manual intervention required
• 🔗 Citations - Reference past observations with IDs (access via http://localhost:37777/api/observation/{id} or view all in the web viewer at http://localhost:37777)
• 🧪 Beta Channel - Try experimental features like Endless Mode via version switching
• 🔌 Custom Provider - Use any OpenAI-compatible API (Ollama, vLLM, Together AI, LiteLLM) as the LLM backend

Documentation

📚 View Full Documentation - Browse on official website

Getting Started

• Installation Guide - Quick start & advanced installation
• Gemini CLI Setup - Dedicated guide for Google's Gemini CLI integration
• Usage Guide - How Claude-Mem works automatically
• Search Tools - Query your project history with natural language
• Beta Features - Try experimental features like Endless Mode

Best Practices

• Context Engineering - AI agent context optimization principles
• Progressive Disclosure - Philosophy behind Claude-Mem's context priming strategy

Architecture

• Overview - System components & data flow
• Architecture Evolution - The journey from v3 to v5
• Hooks Architecture - How Claude-Mem uses lifecycle hooks
• Hooks Reference - 7 hook scripts explained
• Worker Service - HTTP API & Bun management
• Database - SQLite schema & FTS5 search
• Search Architecture - Hybrid search with Chroma vector database

Configuration & Development

• Configuration - Environment variables & settings
• Development - Building, testing, contributing
• Troubleshooting - Common issues & solutions

How It Works

Core Components:

1. 5 Lifecycle Hooks - SessionStart, UserPromptSubmit, PostToolUse, Stop, SessionEnd (6 hook scripts)
2. Smart Install - Cached dependency checker (pre-hook script, not a lifecycle hook)
3. Worker Service - HTTP API on port 37777 with web viewer UI and 10 search endpoints, managed by Bun
4. SQLite Database - Stores sessions, observations, summaries
5. mem-search Skill - Natural language queries with progressive disclosure
6. Chroma Vector Database - Hybrid semantic + keyword search for intelligent context retrieval

See Architecture Overview for details.

MCP Search Tools

Claude-Mem provides intelligent memory search through 4 MCP tools following a token-efficient 3-layer workflow pattern:

The 3-Layer Workflow:

1. search - Get compact index with IDs (~50-100 tokens/result)
2. timeline - Get chronological context around interesting results
3. get_observations - Fetch full details ONLY for filtered IDs (~500-1,000 tokens/result)

How It Works:

• Claude uses MCP tools to search your memory
• Start with search to get an index of results
• Use timeline to see what was happening around specific observations
• Use get_observations to fetch full details for relevant IDs
• ~10x token savings by filtering before fetching details

Available MCP Tools:

1. search - Search memory index with full-text queries, filters by type/date/project
2. timeline - Get chronological context around a specific observation or query
3. get_observations - Fetch full observation details by IDs (always batch multiple IDs)

Example Usage:

// Step 1: Search for index
search(query="authentication bug", type="bugfix", limit=10)

// Step 2: Review index, identify relevant IDs (e.g., #123, #456)

// Step 3: Fetch full details
get_observations(ids=[123, 456])

See Search Tools Guide for detailed examples.

Beta Features

Claude-Mem offers a beta channel with experimental features like Endless Mode (biomimetic memory architecture for extended sessions). Switch between stable and beta versions from the web viewer UI at http://localhost:37777 → Settings.

See Beta Features Documentation for details on Endless Mode and how to try it.

System Requirements

• Node.js: 18.0.0 or higher
• Claude Code: Latest version with plugin support
• Bun: JavaScript runtime and process manager (auto-installed if missing)
• uv: Python package manager for vector search (auto-installed if missing)
• SQLite 3: For persistent storage (bundled)

Windows Setup Notes

If you see an error like:

npm : The term 'npm' is not recognized as the name of a cmdlet

Make sure Node.js and npm are installed and added to your PATH. Download the latest Node.js installer from https://nodejs.org and restart your terminal after installation.

Configuration

Settings are managed in ~/.claude-mem/settings.json (auto-created with defaults on first run). Configure AI model, worker port, data directory, log level, and context injection settings.

See the Configuration Guide for all available settings and examples.

Mode & Language Configuration

Claude-Mem supports multiple workflow modes and languages via the CLAUDE_MEM_MODE setting.

This option controls both:

• The workflow behavior (e.g. code, chill, investigation)
• The language used in generated observations

How to Configure

Edit your settings file at ~/.claude-mem/settings.json:

{
  "CLAUDE_MEM_MODE": "code--zh"
}

Modes are defined in plugin/modes/. To see all available modes locally:

ls ~/.claude/plugins/marketplaces/thedotmack/plugin/modes/

Available Modes

| Mode | Description | |------------|-------------------------| | code | Default English mode | | code--zh | Simplified Chinese mode | | code--ja | Japanese mode |

Language-specific modes follow the pattern code--[lang] where [lang] is the ISO 639-1 language code (e.g., zh for Chinese, ja for Japanese, es for Spanish).

Note: code--zh (Simplified Chinese) is already built-in — no additional installation or plugin update is required.

After Changing Mode

Restart Claude Code to apply the new mode configuration.

Custom Provider Configuration

Claude-Mem supports any OpenAI-compatible API as the LLM backend for observation extraction, including Ollama, vLLM, Together AI, DeepInfra, and LiteLLM.

How to Configure

Edit your settings file at ~/.claude-mem/settings.json:

{
  "CLAUDE_MEM_CUSTOM_BASE_URL": "http://localhost:11434/v1",
  "CLAUDE_MEM_CUSTOM_API_KEY": "",
  "CLAUDE_MEM_CUSTOM_MODEL": "llama-3.1-8b",
  "CLAUDE_MEM_CUSTOM_DISPLAY_NAME": "Ollama",
  "CLAUDE_MEM_CUSTOM_MAX_CONTEXT_MESSAGES": "20",
  "CLAUDE_MEM_CUSTOM_MAX_TOKENS": "100000"
}

| Setting | Description | |---|---| | CLAUDE_MEM_CUSTOM_BASE_URL | Base URL of the OpenAI-compatible API (required) | | CLAUDE_MEM_CUSTOM_API_KEY | API key for authenticated providers (optional) | | CLAUDE_MEM_CUSTOM_MODEL | Model name to use (required, e.g. llama-3.1-8b) | | CLAUDE_MEM_CUSTOM_DISPLAY_NAME | Display name shown in the UI (default: Custom) | | CLAUDE_MEM_CUSTOM_MAX_CONTEXT_MESSAGES | Max messages in context window (default: 20) | | CLAUDE_MEM_CUSTOM_MAX_TOKENS | Max estimated token safety limit (default: 100000) |

You can also configure these settings through the web viewer UI at http://localhost:37777 → Settings.

Examples

Ollama (local):

{
  "CLAUDE_MEM_CUSTOM_BASE_URL": "http://localhost:11434/v1",
  "CLAUDE_MEM_CUSTOM_MODEL": "llama-3.1-8b"
}

Together AI:

{
  "CLAUDE_MEM_CUSTOM_BASE_URL": "https://api.together.xyz/v1",
  "CLAUDE_MEM_CUSTOM_API_KEY": "your-api-key",
  "CLAUDE_MEM_CUSTOM_MODEL": "meta-llama/Llama-3.1-70B-Instruct-Turbo"
}

LiteLLM proxy:

{
  "CLAUDE_MEM_CUSTOM_BASE_URL": "http://localhost:4000",
  "CLAUDE_MEM_CUSTOM_MODEL": "your-model-name"
}

After configuring, select the custom provider in the Viewer UI or set CLAUDE_MEM_CUSTOM_BASE_URL to enable automatic fallback.

Development

See the Development Guide for build instructions, testing, and contribution workflow.

Troubleshooting

If experiencing issues, describe the problem to Claude and the troubleshoot skill will automatically diagnose and provide fixes.

See the Troubleshooting Guide for common issues and solutions.

Bug Reports

Create comprehensive bug reports with the automated generator:

cd ~/.claude/plugins/marketplaces/thedotmack
npm run bug-report

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Update documentation
5. Submit a Pull Request

See Development Guide for contribution workflow.

License

Claude-Mem is licensed under the Apache License 2.0.

We chose Apache-2.0 because durable agentic memory should be easy to embed in developer tools, local agents, MCP servers, enterprise systems, robotics stacks, and production agent harnesses.

See the LICENSE file for full details. See docs/license.md and docs/ip-boundary.md for licensing scope and the open/commercial boundary.

Note on Ragtime: The ragtime/ directory is licensed under the Apache License 2.0. See ragtime/LICENSE for details.

Support

• Documentation: docs/
• Fork Issues: GitHub Issues
• Fork Repository: github.com/MIN202299/claude-mem
• Upstream Repository: github.com/thedotmack/claude-mem
• Original Author: Alex Newman (@thedotmack)
• Official X Account: @Claude_Memory
• Official Discord: Join Discord

Built with Claude Agent SDK | Works with Claude Code | Made with TypeScript

What About $CMEM?

$CMEM is a solana token created by a 3rd party without Claude-Mem's prior consent, but officially embraced by the creator of Claude-Mem (Alex Newman, @thedotmack). The token acts as a community catalyst for growth and a vehicle for bringing real-time agent data to the developers and knowledge workers that need it most. $CMEM: 2TsmuYUrsctE57VLckZBYEEzdokUF8j8e1GavekWBAGS