apache

maka: Keep a Complete Record of AI Agent Work

Apache Maka is a high-performance agent workspace that records every model message, tool call, permission decision, and turn ending. It runs as a desktop app, with TUI and CLI clients, on macOS and preview builds for Windows and Linux.

NewTypeScriptApache-2.0AI AgentsDesktop AppCLI
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Stars
5.8k
Forks
557
Stars, last 29 days
+247
Last commit
today
Contributors
100+

Our take

Newless than six months old and changing fast

Health score

71/100

How it is scored
Activity
84
Community
86
Issues
68
Pull requests
47

+247 stars in the last 29 days

  • Releases more often than 84% of the projects we track
  • Merges more pull requests than 79% of the projects we track
  • More contributors than 78% of the projects we track
  • Slower to merge pull requests than 83% of the projects we track

Maka is a promising, rapidly changing agent workspace with an active contributor base, but its early incubation stage and evolving capabilities call for deliberate evaluation before production adoption.

Good fit if

  • You want agent runs to have a durable, inspectable event record and value recovery from that record.
  • You can supply and configure your own model connection and want desktop, terminal, or evaluation workflows on a shared runtime.
  • You are comfortable testing an incubating project that is receiving frequent code changes and releases.

Look elsewhere if

  • You need a mature, stable product with settled data formats and commands.
  • You require Windows or Linux support beyond preview status.
  • You need a bundled model account or do not want to manage local credentials and model configuration.
All health signals
Last commit2026-10-19 (today)
Commits, last 90 days100+
Releases, last 12 months42 (latest v0.2.1-dev.91.20261018, 2026-10-18, pre-release)
Contributors100+ (top contributor: 36% of commits)
Issues closed, last 90 days13+ (typically closed in 2 days)
Pull requests merged, last 90 days63 (typically merged in 3 days)
Project age5 months

Checked on 2026-10-19 with the GitHub API.

Project history

Daily GitHub snapshots since Oct 7, 2026. History covers stars and forks; health signals are not tracked historically.

Selected snapshot

Stars

5,938

Forks

575

Change since Nov 4, 2026: +5 stars·+2 forks

Overview

Apache Maka is a high-performance agent workspace built around its append-only RuntimeEvent log. It records model messages, tool calls, permission decisions, and turn endings, so the interface, future prompts, and crash recovery can be reconstructed from the run history rather than relying on a transient conversation view. This is aimed at making agent work inspectable and recoverable while measuring task completion and cost.

Maka is a local-first workspace for people who want to bring their own cloud API, local model, or compatible gateway. It offers a desktop app on macOS, with Windows and Linux preview builds, plus TUI and CLI clients that use the same Runtime Host.

Key Features

  • Records agent activity as append-only RuntimeEvents, including model messages, tool calls, permission decisions, and termination.
  • Builds UI, prompts, and crash recovery from the event log, while allowing older tool output to leave the next prompt without deleting the record.
  • Supports user-supplied model connections, including cloud APIs, local models, and compatible gateways.
  • Provides desktop, TUI, and CLI entry points to a shared Runtime Host.
  • Includes an evaluation system that runs experiments and publishes per-task results.
  • Keeps workspace sessions, settings, and run records on the user's machine.
  • Includes sandbox boundaries for tools that write files or run shell commands.

Use Cases

  • Developers can run coding or research tasks through an agent and inspect the recorded tool calls and decisions afterward.
  • Teams evaluating agent harnesses can compare task outcomes using the repository's experiment and evaluation tooling.
  • Users who already have a model API or local model can connect it to a desktop agent workspace without relying on a bundled shared account.
  • Terminal-focused users can run tasks or interact with the agent through the CLI and TUI rather than the desktop interface.

What you need

Detected in the repository

  • Node.js ^22.19.0 || >=24.0.0 (from package.json)
  • Automated checks on GitHub Actions

License in plain words

Apache-2.0permissive

  • Commercial use: yes
  • Modify and redistribute: yes
  • You must keep: the license, the NOTICE file and a note of your changes
  • Share your changes: no
  • Includes an explicit patent grant from the contributors:

A summary, not legal advice: the LICENSE file is what applies.

Getting Started

Requirements include Node.js 22.19 or newer on the 22 line, or Node.js 24 or newer, plus npm and Git. To run the desktop development build:

git clone https://github.com/apache/maka.git
cd maka
npm ci
npm run dev

On first launch, configure a model connection in Settings. See the README for terminal usage, build options, and additional setup details.

Alternatives

  • holaOS: holaOS centers agents alongside apps and integrations with shared local memory, rather than an append-only record of agent execution.
  • craft-agents-oss: Craft Agents focuses on connecting services and files and organizing sessions, with a headless server and CLI for remote use.
ProjectLanguageLicenseStarsStatus
makaTypeScriptApache-2.05.8kNew
holaOSTypeScript–11.4kActive
craft-agents-ossTypeScriptApache-2.07.2kActive

Considerations

Maka is explicitly under active development, and its README warns that data formats, CLI commands, and experimental capabilities may change. The repository is less than six months old and changing quickly, although recent activity includes frequent commits and releases, a broad contributor base, and relatively quick issue and pull request handling. The project is Apache-2.0 licensed and is still in Apache incubation, which is not the same as full ASF endorsement. API keys are stored in a local plaintext credential file readable by the OS account, so teams should review the documented security and privacy boundaries. Windows and Linux are preview platforms, and the README notes that older JSONL transcripts and Electron safeStorage credentials are not imported during upgrades.

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