cc-lens: Local Dashboard for Claude Code Session Analysis
A developer has created cc-lens, a local dashboard tool for analyzing Claude Code usage by reading session data stored locally in ~/.claude/. The tool transforms raw JSON logs into an interactive dashboard that runs entirely on your machine without cloud sync, sign-ups, or telemetry.
Key Features
- Usage overview: sessions, messages, tokens, estimated cost
- Per-project breakdown: see which repositories are using the most tokens
- Full session replay: inspect conversations turn-by-turn with token counts and tool calls
- Cost & cache analytics: stacked charts by model and cache usage
- Activity heatmap: GitHub-style view of when you're using Claude the most
- Memory & plan explorer: browse/edit Claude memory files and saved plans
- Export/import: move dashboards across machines
Installation and Usage
You can run cc-lens instantly with:
npx cc-lensAlternatively, you can clone the repository from GitHub. The tool is designed for developers who want to understand their Claude Code usage patterns, token consumption, and costs without manually parsing JSON files.
📖 Read the full source: r/ClaudeAI
👀 See Also
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Codex Chrome Extension Adds Background Browser Automation Across Tabs
Codex's new Chrome extension on macOS/Windows enables parallel browser task execution in background tabs without taking over the browser — covering debugging flows, dashboards, research, and CRM updates.
Measuring Claude Code MCP Stack: Cache Friendliness vs. Byte Savings, and a 2-Line Fix for Prompt Cache
Greg Shevchenko benchmarks MCP compressors and retrieval layers on two axes: byte savings and cache friendliness. A 2-line fix (sort rg hits, sort map entries) boosts cache from ~0% to 100% with no byte-savings loss. Open-source harness included.
n8n-mcp-lite: MCP server reduces token usage by 80% for Claude with n8n workflows
A new open-source Model Context Protocol server called n8n-mcp-lite helps Claude reason about n8n automation workflows while reducing token usage by approximately 80%. The tool addresses the token-heavy nature of visual node automations by providing targeted workflow scanning and surgical updates.