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Tool connections (MCP)

Claude-Mem

thedotmack/claude-mem

Save coding-session history so an agent can retrieve earlier decisions and fixes in a new conversation.

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What is Claude-Mem?

Prepared by LessAI Tools from public project documentation

Claude-Mem captures work through client hooks, produces summaries, and retrieves relevant history with MCP search tools. It is useful when work continues across sessions and repeating project context becomes tedious. It includes a local service, a database, an implemented MCP search server, and companion skills; support depends on the client integration. Node.js 20+ is required, and setup configures dependencies such as Bun. Summarization uses the selected model or hosted service and can consume subscription quota or incur API charges; a hosted trial is not permanent free access. Review which session content is stored and what is sent to model or sync services before enabling capture.

Claude-Mem setup documentation

Setup requirements have not been reviewed yet. Check the project’s setup guide.

Setup and usage guide ↗

Based on public documentation; not individually installed and tested here.

Claude-Mem use cases

  • Retrieve previous decisions, fixes, and session summaries
  • Read relevant indexes before expanding selected history
  • Connect workflows through MCP search and client hooks

Official project & documentation

View source code ↗Project website ↗Setup and usage guide ↗

The project’s original description

Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More

Alternatives to Claude-Mem for similar tasks

Matches the main use case first, then shared tasks and stars. Setup methods may differ.

  • Graphify — Map code and document relationships to help AI find relevant context.
  • Serena — Help AI find functions and classes and make focused code changes.
  • REA — Reverse Engineer Anything — Let AI investigate how an application's features work and return code and runtime evidence you can check.

Sources and ranking

This directory lists AI development plugins with public source code and a clear purpose. Browse by task, then open an introduction to learn what a project does, who it is for, and what you need to get started. It covers selected projects, not every AI plugin.

How do the three plugin types differ?

Tool connections (MCP) let AI assistants use external tools such as browsers, code repositories and databases. MCP is the protocol used for these connections.

Reusable skills give a compatible AI assistant instructions and guidance for a particular task.

Editor plugins run inside the software you use to write code, adding AI chat, completions or suggested edits.

How does “Most starred” work?

Projects are sorted by their total GitHub stars. Stars indicate interest; they are not downloads, active users or quality scores. A skill pack counts as one project. Daily star growth is not shown without historical records.

What does “Recently updated” mean?

It uses the most recent code push, which may not be a new release. The 7-day filter checks that project update time; ranking still uses all-time stars. Each introduction shows when its star count was collected. Failed updates keep the last saved data.

Introductions are based on public project documentation. These projects have not each been installed and tested here. Check the project documentation for setup, compatibility and service costs. Refreshing this list only reads saved data; it does not start collection.

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