Command-line workbench for managing ZenTao projects in scripts and agents
Manage ZenTao project items from a terminal: login, query Stories or Bugs, convert HTML to Markdown, and run AI Agent skills in-session. windosx publishes this Windows-oriented utilities tool with cross-platform builds for macOS and Linux. It exposes a 50+ command set, persistent session tokens, MCP support, and multiple output formats. Developers, QA, and project managers who prefer scripted or agent-driven workflows gain direct API-like control of ZenTao data from the shell.
What does zentao-cli actually let you do from the shell?
The tool mirrors core ZenTao workflows by exposing commands for Stories, Bugs, Tasks, Products, Projects, Testcases, Releases, Builds, and Documents, drawn from the RESTful API. In practice you run single commands or compose scripts: login with zentao login, query items, filter and sort fields, and emit human-readable tables or Markdown. The CLI also converts ZenTao HTML into Markdown for terminal consumption.
Does it affect system and CI environments in predictable ways?
Designed for both interactive and non-interactive use, the app stores a secure persistent token after initial login, enabling a "zero-auth" experience for subsequent commands. It supports environment variables for credentials, which makes it suitable for CI/CD pipelines and automation agents that need non-interactive access to project data without repeated browser logins.
Is the tool safe to run on production machines and agent runners?
Security features align with token-based workflows: the CLI saves a token instead of passwords and opens a local browser by default for the initial login, with a --no-browser flag available for terminal-only setups. Daily rolling logs are written to system-specific directories, giving administrators a traceable log trail for commands executed by human operators or AI Agents.
How steep is the learning curve for human and AI users?
Offers a mix of task-level commands and AI-focused interfaces: over 50 commands cover routine project management actions while built-in AI Agent Skills and Model Context Protocol support let agents read and act on project data. Casual users can run basic queries; developers building agents can integrate MCP hooks and process filtered outputs programmatically.
Practical CLI for teams and agents, with one operational trade-off
zentao-cli performs reliably as a terminal workbench for scripted project management and AI Agent workflows, especially where token-based persistence and Markdown outputs matter. The single clear trade-off is an operational dependency on the initial browser-based login flow for default authentication; teams using fully headless runners should plan for the --no-browser path or environment-variable credential setup before deployment.
