HiveTerm is a desktop terminal that runs your AI agents (Claude Code, Codex, Gemini, Cline, etc.) alongside servers, builds, and scripts, all orchestrated by a hive.yml file. What sets it apart is Queen, an integrated MCP server that allows agents to create sub-agents, read output from other processes, and send notifications to one another. Add to that per-process resource monitoring, Git integration with a diff viewer, automatic stack detection, and context-separated workspaces.
Hey! 👋
I'm a dev running a small team in Brazil. We use Claude Code, Codex, local servers, builds, all running at the same time. My daily life was 15 terminal tabs, Alt+Tab hell, and zero communication between any of it. Claude Code had no clue my server just crashed. My build logs were buried somewhere I'd already forgotten.
One day I caught myself arranging 4 terminal windows pixel by pixel for the third time that week and thought "this is stupid, I should just build the thing I actually want."
So HiveTerm is that thing. One terminal where your AI agents and dev processes live together. The core idea is Queen, a built-in MCP server that lets agents see each other's output, spawn sub-agents, and send you notifications when stuff finishes or breaks. You drop a hive.yml in your project and everything starts with one command.
Built with Tauri + Rust + React. Native on Mac, Windows and Linux.
I'd genuinely love feedback, especially on what agents or workflows you'd want supported next 🐝
About HiveTerm on Product Hunt
“One workspace for all your AI agents”
HiveTerm launched on Product Hunt on April 16th, 2026 and earned 70 upvotes and 3 comments, placing #35 on the daily leaderboard. HiveTerm is a desktop terminal that runs your AI agents (Claude Code, Codex, Gemini, Cline, etc.) alongside servers, builds, and scripts, all orchestrated by a hive.yml file. What sets it apart is Queen, an integrated MCP server that allows agents to create sub-agents, read output from other processes, and send notifications to one another. Add to that per-process resource monitoring, Git integration with a diff viewer, automatic stack detection, and context-separated workspaces.
On the analytics side, HiveTerm competes within Productivity and Developer Tools — topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how HiveTerm performed against the three products that launched closest to it on the same day.
Who hunted HiveTerm?
HiveTerm was hunted by Ebrahim P. Leite. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of HiveTerm including community comment highlights and product details, visit the product overview.
Ebrahim P. Leite