tessera vs codeg

AI coding agent workspaces compared

tessera and codeg organize multiple AI coding agents and their work in a shared workspace, including parallel tasks and Git worktrees. tessera focuses on coordinating local sessions from several named providers, while codeg centers on an ACP-based interface for conversations, session histories, and delegated work, with desktop and self-hosted deployment options.

tesseracodeg
LanguageTypeScriptRust
LicenseAGPL-3.0Apache-2.0
Stars3134k
Forks29518
Last analyzedOct 14, 2026Oct 19, 2026

Key differences

  • tessera is a TypeScript local workspace for Claude Code, Codex, and OpenCode; codeg is written in Rust and connects agents through the Agent Client Protocol, including compatible ACP agents.
  • tessera emphasizes session organization with persistent tabs, split panes, collections, and Kanban views; codeg combines conversations, files, terminals, and notes on a workspace canvas.
  • tessera includes an agent-facing CLI for launching, inspecting, and prompting sessions; codeg highlights searching, importing, and resuming agent histories and viewing multiple agents' responses together.
  • Both support Git worktrees and reviewing changes, while tessera also describes committing, syncing, publishing branches, and opening pull requests within the workspace.
  • tessera is available as a desktop app, with mobile remote access; codeg offers desktop, self-hosted server, and Docker deployment, with supported mobile clients connecting to the server.
  • tessera uses AGPL-3.0 and reports 310 stars and 29 forks; codeg uses Apache-2.0 and reports 3.8k stars and 487 forks, along with 286 open issues.

Choose tessera if you…

  • need a local workspace centered on Claude Code, Codex, and OpenCode sessions.
  • want persistent tabs, split panes, or Kanban views to organize parallel sessions.
  • prefer built-in session controls for Git workflows and an agent-facing CLI.
Read the tessera analysis →

Choose codeg if you…

  • want to connect built-in or compatible ACP agents in a shared conversation interface.
  • need to search, import, or resume histories across agents and compare their responses.
  • want desktop, self-hosted server, or Docker deployment options.
Read the codeg 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.