synara vs maka

Coding-agent workspaces compared

synara and maka are TypeScript workspaces for running agent-assisted tasks. synara centers on coordinating projects, provider sessions, terminals, previews, and Git review, while maka centers on a shared runtime with an append-only activity log and Desktop, TUI, and CLI interfaces.

synaramaka
LanguageTypeScriptTypeScript
LicenseMITApache-2.0
Stars2k5.8k
Forks310557
Last analyzedOct 3, 2026Oct 19, 2026

Key differences

  • synara organizes work around projects and threads, with integrated file tools, previews, Git workflows, and managed worktrees; maka records model messages, tool calls, permission decisions, and turn endings in append-only RuntimeEvents.
  • synara connects to coding-agent runtimes installed and authenticated locally; maka lets users connect a cloud API, local model, or compatible gateway they provide.
  • synara is a desktop workspace; maka offers an Electron desktop app plus TUI and CLI entry points using the same Runtime Host.
  • synara lists native release targets for Windows and macOS as well as Linux; maka lists macOS without qualification and Windows and Linux as preview platforms.
  • synara is licensed under MIT; maka is licensed under Apache-2.0 and is identified as incubating.
  • Both projects are under active development; synara describes itself as early-stage, while maka warns that data formats, CLI commands, and experimental capabilities may change.

Choose synara if you…

  • need a desktop workspace to coordinate agent sessions across projects and providers.
  • want terminals, previews, file review, and Git actions alongside agent conversations.
  • plan to use locally installed and authenticated coding-agent runtimes or managed worktrees for parallel tasks.
Read the synara analysis →

Choose maka if you…

  • want an append-only record of model and tool activity, including permission decisions.
  • need Desktop, TUI, or CLI access to a shared agent runtime and evaluation tooling.
  • prefer to connect your own cloud API, local model, or compatible gateway and keep run records on your machine.
Read the maka 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.