Is my memory data stored in the cloud?

No, CC-Mem is a local-first system. All captured memories and session data are stored on your local machine to ensure privacy and security.

How do I manually save information to the memory system?

You can use the command '/cc-mem capture ' to explicitly save important snippets, rules, or architectural decisions to the local database.

Does CC-Mem help with Claude's context window limits?

Yes, by allowing you to search and inject specific memories on demand, it helps manage the context window more effectively by only focusing on relevant information.

Can I export my stored memories for documentation?

Yes, you can use the '/cc-mem export' command to output your stored memories into a Markdown file, making it easy to share or archive project context.

CC-Mem is a lightweight plugin for Claude Code that provides a local, rule-driven memory system to store and retrieve session information, helping the AI remember project details.

CC-Mem: Local Context Memory

Name: CC-Mem: Local Context Memory
Author: haiyuan-ai

byhaiyuan-ai

0•

生产力与工作流

Manages persistent local memory for Claude Code sessions to maintain context across complex development tasks.

CC-Mem is a lightweight, local-first memory system designed specifically for Claude Code to solve context loss during long-running development sessions. It utilizes a rule-driven approach and hierarchical storage to allow users to capture, search, and manage session-specific information. By enabling explainable context injection, it ensures that Claude retains crucial knowledge about project architecture, previous decisions, and custom workflows, making the AI more consistent and efficient as projects scale.

主要功能

01Automated memory cleanup and retry mechanisms for failed captures

02Full-text search and statistical analysis of captured session data

03Local-first storage ensuring data privacy and low-latency access

04Rule-driven hierarchical memory for organized context retrieval

05Markdown export capabilities for documentation and portability

060 GitHub stars

使用场景

01Tracking progress and managing task history during complex, multi-day refactoring projects

02Maintaining architectural context and design decisions across multiple Claude Code sessions

03Storing and retrieving project-specific coding patterns or internal documentation

主要功能

01Automated memory cleanup and retry mechanisms for failed captures

02Full-text search and statistical analysis of captured session data

03Local-first storage ensuring data privacy and low-latency access

04Rule-driven hierarchical memory for organized context retrieval

05Markdown export capabilities for documentation and portability

060 GitHub stars

使用场景

01Tracking progress and managing task history during complex, multi-day refactoring projects

02Maintaining architectural context and design decisions across multiple Claude Code sessions

03Storing and retrieving project-specific coding patterns or internal documentation