Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI-coding power users, AI agent developers, automation builders, founders, creators, power users, and any developer running 3+ AI coding-agent sessions in parallel who needs at-a-glance visibility into per-session status -- and who can pair umputun/agterm with macOS 14+ (Sonoma) on Apple Silicon (arm64) for the OS surface, Homebrew (`brew install --cask umputun/apps/agterm`) or GitHub R
Who should use it
Who should skip it
Skip umputun/agterm if the source link, documentation, or setup requirements do not align with your current workflow or stack.
About this signal
umputun/agterm is tracked by RepoRadar as a native macos terminal from umput in the macOS Terminal for AI Coding-Agent Sessions section. It was first seen on 2026-07-07 and last updated on 2026-07-07. The current verdict is 'try now' with a Gold tier and easy setup difficulty. Across RepoRadar's eight signals, umputun/agterm is strongest on workflow potential (9.5) and setup ease (8.8) and weakest on maturity (6.3) — a profile worth weighing against your own priorities. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned umputun/agterm a composite score of 8.0 out of 10, placing it in the Gold tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 1.0 and never affects the composite score or tier. The risk label of 'low' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to vet an AI agent or MCP server before you wire it in for the checklist behind this score.
Risk explanation
The 213* / 20-fork repo is at active maintenance but the app is macOS-only (Apple Silicon + macOS 14+) -- the consumer SHOULD verify the macOS surface before deploying (Linux and Windows are not supported); the `agtermctl` control API exposes a local socket that the consumer SHOULD review before scripting the terminal from another tool; the installable Agent Skill lets a coding agent build its own layout + run overlays + manage windows + show images inline -- the consumer SHOULD review the Agent Skill scope before deploying to a shared workstation; the libghostty engine is built from source on first run -- the consumer SHOULD verify the build environment (macOS 14+ + Xcode 26 + `xcodegen` + Metal Toolchain + Homebrew `[email protected]`) before relying on the build-from-source surface.