maka vs sandbase-harness

Local AI agent runtimes compared

maka and sandbase-harness are TypeScript projects for running AI agents on local machines or self-managed infrastructure. maka centers on a shared runtime with an append-only activity log and desktop, TUI, and CLI clients; sandbase-harness focuses on operating persistent sessions with sandbox, memory, credentials, and MCP support.

makasandbase-harness
LanguageTypeScriptTypeScript
LicenseApache-2.0Apache-2.0
Stars5.8k639
Forks55780
Last analyzedOct 19, 2026Oct 19, 2026

Key differences

  • maka records model messages, tool calls, and permission decisions as append-only RuntimeEvents; sandbase-harness offers persistent sessions with event history, audit, and replay.
  • maka provides a desktop app, TUI, and CLI backed by one Runtime Host; sandbase-harness offers a Console, CLI, TypeScript SDK, and a `/v1` API.
  • maka supports user-provided cloud APIs, local models, and compatible gateways; sandbase-harness lists OpenAI, Anthropic, MiniMax, and OpenAI-compatible providers, and requires a provider API key.
  • maka keeps session data and run records locally; sandbase-harness uses SQLite metadata and local file storage by default, and also supports self-managed deployments with Docker, Kubernetes, or workers.
  • maka is marked as incubating, with Windows and Linux support described as previews; sandbase-harness is less than six months old and has documented compatibility limitations and backend-dependent sandbox boundaries.
  • Both use TypeScript and Apache-2.0; maka has 5.8k stars and 551 forks, while sandbase-harness has 707 stars and 78 forks.

Choose maka if you…

  • want a desktop agent workspace with matching TUI and CLI clients.
  • need append-only records of agent messages, tool calls, and permission decisions.
  • want to connect a cloud API, local model, or compatible gateway and inspect evaluation results.
Read the maka analysis →

Choose sandbase-harness if you…

  • need persistent sessions with replay, memory, credential vaults, and MCP toolsets.
  • plan to run agents on self-managed infrastructure using Docker, Kubernetes, or workers.
  • want a Console, TypeScript SDK, and `/v1` API for operating agent sessions.
Read the sandbase-harness 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.