maka vs tessera

Local AI agent workspaces compared

maka and tessera are local workspaces for running AI coding agents. maka records agent activity through a shared runtime and event log, while tessera organizes sessions from several coding-agent providers around parallel tasks and Git workflows.

makatessera
LanguageTypeScriptTypeScript
LicenseApache-2.0AGPL-3.0
Stars5.8k313
Forks55729
Last analyzedOct 19, 2026Oct 14, 2026

Key differences

  • maka provides Desktop, TUI, CLI, and evaluation tools backed by one Runtime Host; tessera focuses on organizing Claude Code, Codex, and OpenCode sessions.
  • maka records model messages, tool calls, and permission decisions in an append-only event log; tessera emphasizes session views, Git worktrees, and reviewing or publishing code changes.
  • maka connects to a user-configured cloud API, local model, or compatible gateway; tessera depends on provider CLIs installed and authenticated locally.
  • maka uses the Apache-2.0 license; tessera uses AGPL-3.0, whose network-use obligations may matter when offering modified software as a service.
  • maka is an Apache Incubator project and has not made an Apache release; tessera describes team and enterprise capabilities as planned.
  • maka lists Windows and Linux as preview platforms and macOS without that qualification; tessera lists Linux as beta and notes that Windows builds are not code-signed.

Choose maka if you…

  • need a durable record of agent actions, including tool calls and permission decisions.
  • want Desktop, terminal, and evaluation tools sharing one runtime.
  • prefer to configure your own cloud, local-model, or compatible-gateway connection and keep workspace data locally.
Read the maka analysis →

Choose tessera if you…

  • need to coordinate parallel Claude Code, Codex, or OpenCode sessions across projects.
  • want Git worktrees, diff review, and routine Git workflows in the workspace.
  • need mobile access or a CLI for coordinating other agent sessions.
Read the tessera 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.