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Show HN: Claude Code vs. Codex Global Usage Leaderboard

read original get OpenAI Codex API → more articles
Why This Matters

This article highlights the importance of enhanced security and privacy measures in AI development tools, emphasizing encrypted credentials, local data processing, and transparent usage tracking. These features are crucial for building trust with developers and consumers concerned about data security in AI applications.

Key Takeaways

One command authenticates your machine and installs the CostHawk MCP for Claude Code, Codex, Cursor, and Gemini CLI.

Whether you connect via Admin API keys, wrapped proxy keys, or MCP telemetry — your credentials are encrypted, we do not store prompt or code content, and you control what gets shared.

AES-256 key encryption Admin API keys are encrypted at rest with AES-256-GCM. We never store or see your keys in plaintext.

Wrapped key isolation Proxy your API calls through CostHawk. Your real provider keys never touch your codebase or client devices.

Local-first parsing MCP telemetry is computed locally from supported developer-tool data directories before anything leaves your machine.

No prompt storage We only persist usage metadata: token counts, models, timestamps, and hashed project IDs. Prompt and code content is never stored.

Preview before upload Dry-run syncs show exactly what would be sent, with payload previews and optional file lists for full transparency.