synara vs Kun

Local-first workspaces for coordinating AI agents

synara and Kun are local-first workspaces for directing AI agents and managing the work around them. synara focuses on coding-agent sessions, project files, terminals, previews, and Git review, while Kun also supports writing, design, research, and automation through a desktop GUI and terminal TUI.

synaraKun
LanguageTypeScriptTypeScript
LicenseMITNOASSERTION
Stars2k6.3k
Forks310595
Last analyzedOct 3, 2026Oct 4, 2026

Key differences

  • synara connects to coding-agent runtimes installed and authenticated on your machine; Kun uses a configured compatible model provider, including APIs, subscriptions, compatible services, or self-hosted models.
  • synara centers on coding projects and agent sessions; Kun also provides Work mode for documents and research, a design canvas, and Rooms for multi-agent collaboration.
  • Kun offers a terminal TUI that shares a runtime with its desktop GUI; synara is described as a desktop workspace.
  • Both projects use TypeScript, but synara lists an MIT license while Kun’s repository metadata says NOASSERTION; its README describes PolyForm Noncommercial terms and says commercial use requires separate written authorization.
  • The supplied repository figures list 2k stars and 310 forks for synara, compared with 6.3k stars and 595 forks for Kun.
  • synara’s README describes it as early-stage, with APIs and interface details under active development.

Choose synara if you…

  • want a desktop workspace centered on coding-agent sessions, project files, terminals, previews, and Git review.
  • already use locally installed agent runtimes and want to keep their existing authentication and subscriptions.
  • need managed worktrees to isolate parallel coding tasks or hand work between providers.
Read the synara analysis →

Choose Kun if you…

  • want one workspace for coding, writing, design, research, and automation.
  • need tasks and approvals to continue between a desktop GUI and terminal TUI.
  • want options for multi-agent discussions, delegated work, and review, or for configuring a compatible model provider.
Read the Kun analysis →

Compare the numbers side by side, or add more projects

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.