codeburn (getagentseal/codeburn) is an open-source AI project on GitHub. Repository summary: See where your AI coding tokens go. Interactive TUI dashboard for Claude Code, Codex, and Cursor cost observability. Its focus includes MCP and tool-calling integration, evaluation and observability, developer-centric engineering workflows. It is suitable for extension, integration, and iterative delivery in real workflows.
License
MIT
Stars
6,233
Homepage
https://codeburn.app/Features
- Core capability: See where your AI coding tokens go. Interactive TUI dashboard for Claude Code, Codex, and Cursor cost observability.
- Provides MCP or tool-calling integration
- Includes evaluation, tracing, or observability capabilities
- Built for code generation, debugging, or engineering integration
- Repository: getagentseal/codeburn
- Primary language: TypeScript
Use Cases
- Connects external systems into agent workflows
- Used for AI quality monitoring and regression evaluation
- Supports AI engineering build-and-iterate workflows for dev teams
- Build internal AI workflow prototypes with codeburn
- Validate codeburn in production-like engineering scenarios
- Building AI development workflows
FAQ
Teams should first define integration boundaries and call patterns, then map repository capabilities into concrete interfaces, parameters, and access rules. GitHub repository: https://github.com/getagentseal/codeburn. Community traction is around 6,154 stars. License: MIT.
It usually works as an execution component or capability layer, with common deployment fits such as: Connects external systems into agent workflows, Used for AI quality monitoring and regression evaluation, Supports AI engineering build-and-iterate workflows for dev teams.
