Agents Elements: A macOS Dashboard for Claude Code & Codex Installations
Agents Elements is a native SwiftUI macOS app that gives you visibility into everything Claude Code and Codex have installed locally — skills, subagents, commands, plugins, MCP servers, hooks, and active sessions. It scans ~/.claude and ~/.codex and presents a searchable dashboard.
Key Features
- All installed elements in one searchable list with rendered Markdown previews
- Session management: shows live, resumable, and stale sessions with token usage and a copy-paste resume command
- Token & cost analytics: Claude and GPT side by side
- Hooks/automation audit: what runs behind your back, including cleanup sweeps
- Permission visibility: each subagent's tools, each plugin's contributions
- Enable/disable plugins & skills from the UI — path-locked, backs up config first
Technical Details
- Built entirely by Claude in Claude Code — the author only steered
- Zero dependencies, reads everything locally, uploads nothing
- License: MIT, open source
- Repo: github.com/LasaleFamine/agents-elements
Who It's For
Developers who use Claude Code or Codex and want to audit and manage what their AI agents have installed without digging through dotfiles.
📖 Read the full source: r/ClaudeAI
👀 See Also
Exploring AI with Tiny Bots: Understanding AI Agents Through Nanobot Tutor
OpenClaw community member shares insights with the 'Nanobot Tutor', a miniature framework aimed at demystifying AI agent functionality. Discover how diving into this compact learning environment unveils the workings of intelligent agents.
MCP Support Merged into llama.cpp with New WebUI Features
The Model Context Protocol (MCP) pull request for llama.cpp has been merged, adding MCP support, tool calls, an agentic loop, and a server selector to the llama-server/WebUI side.
Aurelius: A React Framework Built with 48 Claude Code Agents and Figma-to-React Pipeline
Aurelius is an open-source React framework that uses 48 Claude Code agents organized hierarchically to autonomously build React applications from Figma designs. The framework enforces TDD, visual QA with pixel-diff comparison, and quality gates before deployment.
MCP as Observability Interface: Connecting AI Agents to Kernel Tracepoints
The Model Context Protocol (MCP) is emerging as the interface between AI agents and infrastructure telemetry, with Datadog shipping an MCP server and Qualys flagging security concerns. The article explores two approaches: wrapping existing platforms or building MCP-native observability that connects directly to kernel tracepoints.