{"name":"Apache Maka: A High-Performance Agent Workspace for AI Tasks","description":"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.","github":"https://github.com/apache/maka","url":"https://osrepos.com/repo/apache-maka","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/apache-maka","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/apache-maka.md","json":"https://osrepos.com/repo/apache-maka.json","topics":["AI Agent","Agent Workspace","LLM","TypeScript","Apache Project","Desktop App","CLI Tool","Event Sourcing"],"keywords":["AI Agent","Agent Workspace","LLM","TypeScript","Apache Project","Desktop App","CLI Tool","Event Sourcing"],"stars":null,"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.","content":"## Introduction\nApache 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.\n\n## Why Use It & Key Features\nMaka stands out with its commitment to measurable performance and a unique approach to agent operations:\n*   **Measured, not claimed:** Maka is rigorously benchmarked against other agent harnesses using official verifiers, with per-task results published for full transparency.\n*   **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.\n*   **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.\n*   **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.\n\n## Installation\n### Desktop Nightly\nFor 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.\nYou can find the installers and platform status on the official [downloads page](https://maka.apache.org/en/downloads/ \"Maka Downloads Page\" target=\"_blank\").\n\n### Build from Source\nTo compile and run Maka directly from source, you'll need:\n*   Node.js 22.19 or newer (CI uses Node.js 24)\n*   npm (current `packageManager` is npm 11)\n*   Git\n*   `ripgrep` (used by Runtime's `Grep` tool)\n\nFollow these steps to start the Desktop development environment:\nsh\ngit clone https://github.com/apache/maka.git\ncd maka\nnpm ci\nnpm run dev\n\nFor 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`.\n\n## Examples\n### First Run Setup\nUpon first launch, Maka requires model configuration:\n1.  Open `Settings ? Models`.\n2.  Add an API, local-model, or supported account connection.\n3.  Test the connection and choose a default model.\n4.  Return to the workspace and start a task.\n\n### CLI Usage\nAfter building the workspaces (`npm run build`), you can use the TUI or run commands:\nsh\nnpm run cli:dev\nnpm run cli:dev -- run \"Summarize this repository and identify its most important risk\"\nnpm run cli:dev -- run --graph \"Implement two independent slices, integrate them, then review the result\"\nnpm run cli:dev -- --help\n\nThe TUI also supports commands like `/graph on`, `/graph off`, and `/graph <task>`.\n\n## Links\n*   **Official Website:** [https://maka.apache.org/en/](https://maka.apache.org/en/ \"Maka Official Website\" target=\"_blank\")\n*   **Documentation:** [https://maka.apache.org/en/](https://maka.apache.org/en/ \"Maka Documentation\" target=\"_blank\") (also see the [README on GitHub](https://github.com/apache/maka#documentation \"Maka Documentation on GitHub\" target=\"_blank\"))\n*   **Downloads:** [https://maka.apache.org/en/downloads/](https://maka.apache.org/en/downloads/ \"Maka Downloads Page\" target=\"_blank\")\n*   **GitHub Repository:** [https://github.com/apache/maka](https://github.com/apache/maka \"Maka GitHub Repository\" target=\"_blank\")","metrics":{"detailViews":0,"githubClicks":1},"dates":{"published":null,"modified":"2026-09-11T12:41:20.000Z"}}