Apache Maka: A High-Performance Agent Workspace for AI Tasks
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Summary
Apache Maka is an incubating project from The Apache Software Foundation, offering a high-performance agent workspace designed to meticulously record all agent activities. It provides a local-first environment for AI agents, allowing users to bring their own models and ensuring transparent, measurable task completion. This project aims to set a new standard for agent reliability and accountability.
Repository Information
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Introduction
Apache Maka (Incubating) is a high-performance agent workspace designed to keep a complete, verifiable record of everything an AI agent does. As an incubating project under The Apache Software Foundation, Maka focuses on transparency and accountability in AI task completion, providing a robust environment for developers and researchers.
Why Use It & Key Features
Maka stands out with its commitment to measurable performance and a unique approach to agent operations:
- Measured, not claimed: Maka is rigorously benchmarked against other agent harnesses using official verifiers, with per-task results published for full transparency.
- The log is the runtime: Every action, from model messages to tool calls and permission decisions, is recorded as an append-only
RuntimeEvent. This log serves as the single source of truth for the UI, subsequent prompts, and crash recovery. - Your machine, your model: Maka operates on a local-first principle, keeping sessions, settings, and run records on your machine. Users can integrate their preferred models, whether a cloud API, a local model, or a compatible gateway.
- One Runtime Host: Desktop, TUI, CLI, and evaluation environments all function as thin clients of a single, authoritative execution host, ensuring consistent behavior across platforms.
Installation
Desktop Nightly
For developers and testers, daily builds are available for macOS (Apple Silicon and Intel), Windows x64, and Linux x64/arm64. Note that Windows and Linux builds are unsigned previews and not intended for production use. You can find the installers and platform status on the official downloads page.
Build from Source
To compile and run Maka directly from source, you'll need:
- Node.js 22.19 or newer (CI uses Node.js 24)
- npm (current
packageManageris npm 11) - Git
ripgrep(used by Runtime'sGreptool)
Follow these steps to start the Desktop development environment:
git clone https://github.com/apache/maka.git
cd maka
npm ci
npm run dev
For a full build before starting Electron, use npm run dev:full. For peer-enabled development, use npm run dev:peer or npm run dev:full:peer.
Examples
First Run Setup
Upon first launch, Maka requires model configuration:
- Open
Settings ? Models. - Add an API, local-model, or supported account connection.
- Test the connection and choose a default model.
- Return to the workspace and start a task.
CLI Usage
After building the workspaces (npm run build), you can use the TUI or run commands:
npm run cli:dev
npm run cli:dev -- run "Summarize this repository and identify its most important risk"
npm run cli:dev -- run --graph "Implement two independent slices, integrate them, then review the result"
npm run cli:dev -- --help
The TUI also supports commands like /graph on, /graph off, and /graph <task>.
Links
- Official Website: https://maka.apache.org/en/
- Documentation: https://maka.apache.org/en/ (also see the README on GitHub)
- Downloads: https://maka.apache.org/en/downloads/
- GitHub Repository: https://github.com/apache/maka
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