# Apache Maka: A High-Performance Agent Workspace for AI Tasks This repository profile is provided by osrepos.com, an open source repository discovery platform. Source: osrepos.com Repository profile: https://osrepos.com/repo/apache-maka Generated for open source discovery and AI-assisted research. 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 OSRepos URL: https://osrepos.com/repo/apache-maka ## 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. ## Topics - AI Agent - Agent Workspace - LLM - TypeScript - Apache Project - Desktop App - CLI Tool - Event Sourcing ## Repository Information Last analyzed by OSRepos: Fri Sep 11 2026 13:41:20 GMT+0100 (Western European Summer Time) Detail views: 0 GitHub clicks: 1 ## Safety Notice OSRepos shares public repositories for knowledge and discovery only. Review source code, dependencies, licenses, and security implications before running or installing anything. ## Content ## 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](https://maka.apache.org/en/downloads/ "Maka Downloads Page" target="_blank"). ### 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 `packageManager` is npm 11) * Git * `ripgrep` (used by Runtime's `Grep` tool) Follow these steps to start the Desktop development environment: sh 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: 1. Open `Settings ? Models`. 2. Add an API, local-model, or supported account connection. 3. Test the connection and choose a default model. 4. 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: sh 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 `. ## Links * **Official Website:** [https://maka.apache.org/en/](https://maka.apache.org/en/ "Maka Official Website" target="_blank") * **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")) * **Downloads:** [https://maka.apache.org/en/downloads/](https://maka.apache.org/en/downloads/ "Maka Downloads Page" target="_blank") * **GitHub Repository:** [https://github.com/apache/maka](https://github.com/apache/maka "Maka GitHub Repository" target="_blank")