Compare AI Usage Tracker vs. Preloop in 2026

Preloop

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Description

AI Usage Tracker is a macOS application designed for those who keep an eye on the activity of AI coding tools and local models while they work. It features a compact interface that can be positioned at the top, bottom, left, or right edge of the screen, presenting important information such as account limits, reset times, and the activity of various agents. Users are able to track their session and weekly usage statistics, receive notifications about resets, and easily switch back to a tracked session when an agent requires further input. This application supports a range of tools including Claude, Codex, Cursor, Gemini, OpenCode, Kimi, Ollama, and LM Studio, with available metrics differing based on the provider and account specifics. Additionally, for compatible local models, it can provide insights into context utilization and generation speeds, and allows the configuration of separate work and personal profiles for select services. To use this application, users must have macOS 15 or newer, and it is compatible with both Apple silicon and Intel-based Macs. Overall, AI Usage Tracker is an essential tool for anyone looking to optimize their interaction with AI coding technologies.

Description

Preloop serves as an open-source control plane designed for AI agents that perform tangible actions. It integrates a multi-layered security approach featuring an MCP firewall for managing tool access, an AI model gateway that ensures cost-effectiveness, safety, and accountability, along with policy-as-code that incorporates human oversight, all while providing runtime session visibility and audit trails—all within a self-hosted environment. Given the rapid capabilities of AI agents to deploy code, modify infrastructure, manage financial transactions, access production data, and incur model costs almost instantaneously, Preloop empowers teams to regulate agent activities, monitor expenditures, and determine which actions necessitate human consent. It is compatible with a variety of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents that adhere to MCP standards. Additionally, access rules can evaluate not only the tool names but also arguments and context, utilizing CEL expressions to establish detailed conditions. Furthermore, teams have the flexibility to initiate with observability features and progressively introduce approval and denial protocols without the need for SDKs or extensive modifications to existing applications, thus streamlining the implementation process. This comprehensive approach ensures that organizations remain in control of their AI agents' functionalities and impacts.