Overview
agentsview is a powerful, local-first solution for managing and analyzing your AI coding agent sessions. Designed for developers, it provides a unified platform to browse, search, and track the costs associated with tools like Claude Code, Codex, and over 20 other popular agents. With a single binary and no account requirements, all your data stays local and secure.
Key Features
- Unified Session Intelligence: Gain insights across all your AI coding agents from one central dashboard.
- Local-First & Private: All data is processed and stored locally on your machine, ensuring privacy and security. No external accounts or cloud dependencies are required for core functionality.
- Blazing Fast Cost Tracking: Experience a 100x faster replacement for traditional cost monitoring tools. agentsview leverages indexed SQLite databases for lightning-fast queries on token usage and compute costs.
- Comprehensive Agent Support: Integrates seamlessly with Claude Code, Codex, Copilot CLI, Gemini CLI, and many more (over 20 agents supported out-of-the-box).
- Powerful Search & Analytics: Features full-text search across all message content, detailed token usage and cost breakdowns, and an analytics dashboard with activity heatmaps and velocity metrics.
- Flexible Deployment: Easily installable via a single script, desktop app, or Docker image. Supports advanced configurations like PostgreSQL synchronization for team dashboards and DuckDB mirroring for portable analytics.
- Keyboard-First UI: Navigate and interact with your agent sessions efficiently using keyboard shortcuts.
Typical Use Cases
- Cost Optimization: Monitor token consumption and associated costs for various AI coding agents to identify areas for budget optimization.
- Session Discovery & Analysis: Quickly search and review past agent interactions, understand how agents are used, and identify patterns in development workflows.
- Team Collaboration (with PostgreSQL): Share session data and cost insights across your team by synchronizing with a central PostgreSQL instance.
- Research & Development: Analyze agent performance, tool usage, and session archetypes to inform future AI development and agent design.
- Developer Productivity: Streamline the process of managing and understanding AI agent outputs with a consolidated, fast, and intuitive interface.
