Apache Maka (Incubating)

Incubating at The Apache Software Foundation

A local-first Agent workspace built for real work. Maka inspects projects, runs tools under a sandbox boundary, and records model messages and tool calls as recoverable execution facts — on your machine, through one Runtime Host.

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Why Maka

Your machine, your data

Sessions, settings, and run records stay local by default. You bring the model: a cloud API, a local model, or a compatible gateway.

The record is kept

Model messages, tool calls, tool results, and how a turn ended are written down. The UI and the next model call are views of that record, not the only copy.

Shorter context is not deleted history

Maka can omit old tool output from the next prompt without throwing away the saved evidence.

One place runs the agent

Desktop, the terminal, and Maka evaluation all go through Runtime Host. Eval only owns the experiment and its scores.

Surfaces

Entry point	Best for	Current capability
Desktop	Daily interaction, file and Artifact workflows, model and permission setup	Electron + React with streaming sessions, tool timelines, branching, search, and recovery
TUI / CLI	Using Maka in the current project directory or running one non-interactive Turn	`maka`, `maka run`; shares workspace and model connections with Desktop
Eval	Reproducible benchmark experiments across Maka and external subjects	`maka eval run --out `

Current capabilities

Agent Runtime

Multiple model connections, streaming output, thinking, usage, and clearer provider errors
Built-in tools: `Read`, `Write`, `Edit`, `Bash`, `Glob`, `Grep`. Computer Use and catalog skills are optional and not on by default
Tools that leave the sandbox must be approved; runs can be aborted; failures are classified
A durable execution record, crash recovery, and optional resume of an interrupted turn

Desktop workspace

Create, archive, search, rename, retry, regenerate, and branch sessions from a Turn
Artifact lists and previews, workspace instructions, model settings, and sandbox settings
Local memory and web search when configured
Chat apps (IM bots) are experimental

Evaluation

Declarative multi-arm experiments expanded into task × repetition × subject cells
Immutable per-cell attempts with targeted infrastructure replacement and earliest-valid selection
A small result kernel for score, normalized usage, attributable cost, duration, status, failure reason, and artifacts
Maka subjects execute only through Runtime Host; external subjects use generic external subject adapters

Quick Start

Apache Maka has not made an Apache release yet. Build and run Maka from source:

                git clone https://github.com/apache/maka.git

                cd maka

                npm ci

                npm run dev

Requirements: Node.js 22.19 or newer, npm, Git, `ripgrep`

For Terminal entry points:

                npm run build

                npm run cli:dev

                npm run cli:dev -- run "Summarize this repository"