apache/makaPublic

Apache Maka (Incubating) is a high-performance agent workspace that keeps a complete record of everything it did.

AI summary: A local-first AI agent workspace that records model messages and tool executions as an append-only log.

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TypeScriptApache-2.0Created May 27, 2026Last push today+553 stars this week+3K this month

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since Aug 22, 2026
02K4KAug 2026Aug 2026Sep 2026Sep 2026
5.2K stars as of Sep 10, 2026, tracked back to Aug 22, 2026.

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Signals and awards

derived from tracked data
  • Breakout launch

    5,198 stars in 106 days

  • Rising fast

    +553 stars this week

  • Very active

    3,886 commits in 52 weeks

  • Community-driven

    ~103 contributors

  • Well documented

    High community health score

  • Permissive license

    Apache-2.0

  • Repeat trending

    22 trending appearances

What maka does

Maka is a local-first workspace designed for executing and auditing complex AI agent tasks. It replaces ephemeral chat contexts with a durable, append-only Runtime Event Log that strictly records all model messages, tool calls, permission decisions, and execution results. This architecture ensures that every agent interaction—whether inspecting projects or generating artifacts—is highly transparent, recoverable, and reproducible. By keeping sessions and settings on the local machine and allowing flexible model connections (cloud API or local), it provides a secure environment for agents to perform real work while remaining fully auditable.

AI engineers, security-conscious developers, and researchers who require an auditable, local-first environment to run and evaluate autonomous agent tasks.

  • Append-Only Execution Log: Record every model message, tool call, and termination event as immutable facts in a durable runtime log.
  • Local-First Architecture: Store all sessions, configurations, and run records locally to maintain data privacy and offline capability.
  • Flexible Model Support: Connect seamlessly to cloud APIs, locally hosted models, or compatible gateways without changing the core workflow.
  • Multi-Interface Access: Execute agent tasks via a dedicated macOS desktop app, a terminal TUI, or a non-interactive CLI.
  • Auditable Tool Execution: Enforce controlled permissions and explicitly log every tool invocation and result for complete execution transparency.

Where teams use it

Auditable Agent Workflows

Running complex, multi-step agent tasks where every tool execution and state change must be verifiable and reversible.

Local-First Development

Executing AI coding assistants on private, sensitive codebases without exposing the execution context to a hosted cloud workspace.

Agent Evaluation Tracking

Using the append-only event log to precisely analyze an agent's decision-making process and tool usage for model evaluation.

Recoverable AI Sessions

Resuming long-running, interrupted agent tasks flawlessly by replaying the deterministic execution log from the local machine.

Getting started: Refer to the repository documentation for building the macOS desktop application or CLI.

README

main branch

Maka Apache Maka (Incubating)

Incubating at The Apache Software Foundation

GitHub stars License: Apache 2.0 macOS Apple Silicon and Intel Windows unsigned preview Linux unsigned preview DeepWiki: third-party AI-generated docs 中文文档

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.

Download Desktop Nightly
Daily builds from main for developers and testers. Not an ASF release, not intended for production use.

Maka — Your work. Your agent.

Note

Apache Maka (Incubating) is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator PMC. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. DISCLAIMER-WIP records the issues the project is currently aware of.

Important

Maka is under active development. Data formats, CLI commands, and experimental capabilities may still change.

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.

Read Maka Backend Architecture for the design.

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 <spec> --out <directory>

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. See IM onboarding.

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

Releases and downloads

Apache Maka has not made an Apache release yet. Everything currently published from this repository or from a package registry was produced before or during incubation, is not an Apache Software Foundation release, and has not been reviewed or voted on by the Incubator PMC.

Once Apache releases exist, the official release is the source release published by the ASF and approved by the podling PPMC and the Incubator PMC. A package built from that source and distributed elsewhere, for example through a package registry or as a Desktop installer, is a convenience artifact rather than the release itself, and it is valid only when it is built from an approved source release. .github/ASF_SOURCE_RELEASE.md holds the candidate contract, signing path, and verification steps.

Desktop Nightly is built daily from main for developers and testers. Choose the newest Maka Desktop Nightly prerelease; after installation, the app updates automatically on the Nightly channel. It is not an ASF release and is not intended for production use. Desktop currently targets Apple Silicon Macs (arm64). Intel Macs and Linux are not supported yet. Windows is an unsigned preview, not a supported release tier.

Requirements

  • Node.js 22.19 or newer (CI uses Node.js 24);
  • npm (the lockfile and scripts use npm; the current packageManager is npm 11);
  • Git;
  • ripgrep, used by Runtime's Grep tool.

Start Desktop

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

npm run dev starts the Desktop development environment with HMR. To build every workspace before starting Electron, use:

npm run dev:full

Direct Peer and Peer Mesh development additionally requires Rust stable 1.98 or newer and the platform linker (Xcode Command Line Tools on macOS, MSVC Build Tools on Windows). Use the peer-enabled entry point so the native addon is built before Desktop starts:

npm run dev:peer       # HMR
npm run dev:full:peer  # full build

If dependencies were installed with ELECTRON_SKIP_BINARY_DOWNLOAD=1, install the Electron platform binary before starting:

node node_modules/electron/install.js

First run

Maka does not bundle a shared model account. On first launch:

  1. Open Settings → Models;
  2. Add an API, local-model, or supported account connection;
  3. Test it and choose a default model;
  4. Return to the workspace and start a task.

The app distinguishes configured, send-ready, and experimental connection states. An account flow that is not wired into Runtime is not presented as a usable model.

Terminal entry points

For the public npm package, see the CLI installation and usage guide. The commands below run the development CLI from a source checkout.

Build the workspaces first:

npm run build

Then start the TUI or run one Turn:

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 accepts /graph on, /graph off, and /graph <task>. Non-interactive --graph runs wait for the durable Graph to finish before printing the final supervisor output. Graph implementation operators use isolated Git worktrees, so the source project must be a clean Git worktree.

The repository CLI uses the same Maka Dev profile as a development Desktop build. The released maka binary continues to use the Maka profile; the two profiles are not copied or synchronized automatically. Evaluation specs and adapters live in packages/eval.

Architecture

The backend spine is:

Desktop / TUI / CLI → Runtime Host → SessionManager → AgentRun
                                             ↓
                         Model + Tool Runtime → Runtime Event Log
                                             ↓
                              Context / Session / UI projections

Experiment → Cells → Attempts → Results
                    ↓
       Runtime Host executes Maka subjects

Start with ARCHITECTURE.md. It provides the system map, code boundaries, problem-oriented reading paths, and six bilingual deep dives.

Repository layout

apps/desktop/          Electron main / preload / React renderer

packages/core/         Pure contracts for Sessions, Events, Permissions, and Connections
packages/storage/      SQLite operational state, configuration, and payload stores
packages/mcp/          Provider-neutral Model Context Protocol client integration
packages/runtime/      AgentRun, model adapters, tools, context, and recovery
packages/runtime-host/ Single-owner Runtime Host lifecycle, protocol, and client bootstrap
packages/eval/         Experiment cells, attempts, results, and executor/subject adapters
packages/computer-use/ Computer-use backend selection, host lifecycle, and protocol adapters
packages/cli/          TUI and non-interactive CLI
packages/ui/           Shared conversation, Markdown, Artifact, and UI primitives

docs/                  Architecture, product, security, privacy, and test contracts
scripts/               Build hygiene, visual checks, smoke tests, and release helpers

Local data and recovery

Workspace data lives under Electron userData by default:

<Electron userData>/workspaces/default/
  runtime.sqlite
  connection-catalog.json
  credential-vault.json
  settings.json
  artifacts/
  • API keys and similar secrets are a local plaintext file (credential-vault.json), readable only by your OS account. The renderer never sees them.
  • Tools that write files or run a shell must pass the sandbox boundary first.
  • runtime.sqlite is the live record. Older JSONL transcripts and Electron safeStorage credential files are not imported; an upgraded workspace can show empty threads, and those credentials must be entered again.
  • Resuming an interrupted turn is off by default. Set MAKA_RUNTIME_SAFE_BOUNDARY_RESUME=1 only if you want Desktop Safe resume, CLI /resume, and startup auto-resume — those calls hit the model and use tokens.

Details: SECURITY.md, privacy, resume.

Development and verification

Before sending a change, read CONTRIBUTING.md.

Common repository-level commands:

npm run build
npm run typecheck
npm test
npm run check:release

Run one workspace in isolation:

npm --workspace @maka/runtime run test:dist
npm --workspace @maka/eval run test:dist
npm --workspace @maka/desktop run test:dist

Use refresh:model-metadata to fetch the current catalog from models.dev, update the committed snapshot, and regenerate the derived TypeScript files. A refresh fails closed when any committed model, capability, provider override, or pricing field disappears; after reviewing an intentional upstream removal, acknowledge it with npm run refresh:model-metadata -- --accept-upstream-removals. sync:model-metadata is intentionally offline: it only regenerates those files from the committed snapshot. Keep access-path-specific overrides in model-metadata.ts; do not edit the generated files by hand.

npm run refresh:model-metadata
npm --workspace @maka/core run test:dist

Desktop real-window and visual verification:

npm --workspace @maka/desktop run e2e
npm --workspace @maka/desktop run smoke:real-window

Before submitting code, run typecheck, build, and focused tests proportionate to the change, followed by git diff --check.

Documentation

License

Maka is licensed under the Apache License 2.0. See NOTICE for attribution information. Third-party components remain subject to their respective licenses and notices.

Apache Maka, Maka, Apache, the Apache feather, and the Apache Maka project logo are either registered trademarks or trademarks of The Apache Software Foundation.

View on GitHub

Recent activity

commits and pull requests

Releases and announcements

4 total
  1. Maka Desktop Nightly 0.2.0-dev.12.20260901v0.2.0-dev.12.20260901Sep 1, 2026pre-release210 downloads

    Developer Snapshot 0.2.0-dev.12.20260901 This Desktop Nightly was built from 6b9de442f653759fef68627ba3cb0ed1d705bcfc for development and testing. It is not an Apache Release and has not been approved by an ASF release vote. The packaged applications carry the repository DISCLAIMER-WIP and Apache License 2.0 materials. They may be unstable and are not intended as a stable release for general users.

  2. Maka Desktop Nightly 0.2.0-dev.9.20260831v0.2.0-dev.9.20260831Aug 31, 2026pre-release76 downloads

    Developer Snapshot 0.2.0-dev.9.20260831 This Desktop Nightly was built from bd951aa8819c5c03e39d2878f6866ef5aa53a075 for development and testing. It is not an Apache Release and has not been approved by an ASF release vote. The packaged applications carry the repository DISCLAIMER-WIP and Apache License 2.0 materials. They may be unstable and are not intended as a stable release for general users.

  3. Maka Desktop Nightly 0.2.0-dev.11.20260831v0.2.0-dev.11.20260831Aug 31, 2026pre-release357 downloads

    Developer Snapshot 0.2.0-dev.11.20260831 This Desktop Nightly was built from c76fbda74fb8e06ea8f8a0d4c682b992d8060f53 for development and testing. It is not an Apache Release and has not been approved by an ASF release vote. The packaged applications carry the repository DISCLAIMER-WIP and Apache License 2.0 materials. They may be unstable and are not intended as a stable release for general users.

  4. Maka Desktop Nightly 0.2.0-dev.10.20260831v0.2.0-dev.10.20260831Aug 31, 2026pre-release42 downloads

    Developer Snapshot 0.2.0-dev.10.20260831 This Desktop Nightly was built from 29d02dc218078297215f6792de3afb55b76386da for development and testing. It is not an Apache Release and has not been approved by an ASF release vote. The packaged applications carry the repository DISCLAIMER-WIP and Apache License 2.0 materials. They may be unstable and are not intended as a stable release for general users.

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3.9K commits in the last 52 weeks.

When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 39 commitsSun 1:00 — 30 commitsSun 2:00 — 20 commitsSun 3:00 — 13 commitsSun 4:00 — 8 commitsSun 5:00 — 2 commitsSun 6:00 — 4 commitsSun 7:00 — 7 commitsSun 8:00 — 12 commitsSun 9:00 — 4 commitsSun 10:00 — 21 commitsSun 11:00 — 25 commitsSun 12:00 — 22 commitsSun 13:00 — 28 commitsSun 14:00 — 21 commitsSun 15:00 — 31 commitsSun 16:00 — 23 commitsSun 17:00 — 21 commitsSun 18:00 — 30 commitsSun 19:00 — 31 commitsSun 20:00 — 30 commitsSun 21:00 — 33 commitsSun 22:00 — 17 commitsSun 23:00 — 23 commitsMon 0:00 — 28 commitsMon 1:00 — 18 commitsMon 2:00 — 11 commitsMon 3:00 — 6 commitsMon 4:00 — 3 commitsMon 5:00 — 0 commitsMon 6:00 — 1 commitsMon 7:00 — 0 commitsMon 8:00 — 9 commitsMon 9:00 — 6 commitsMon 10:00 — 5 commitsMon 11:00 — 7 commitsMon 12:00 — 19 commitsMon 13:00 — 13 commitsMon 14:00 — 28 commitsMon 15:00 — 22 commitsMon 16:00 — 31 commitsMon 17:00 — 34 commitsMon 18:00 — 25 commitsMon 19:00 — 25 commitsMon 20:00 — 36 commitsMon 21:00 — 31 commitsMon 22:00 — 22 commitsMon 23:00 — 25 commitsTue 0:00 — 18 commitsTue 1:00 — 16 commitsTue 2:00 — 17 commitsTue 3:00 — 25 commitsTue 4:00 — 15 commitsTue 5:00 — 4 commitsTue 6:00 — 1 commitsTue 7:00 — 0 commitsTue 8:00 — 12 commitsTue 9:00 — 11 commitsTue 10:00 — 10 commitsTue 11:00 — 20 commitsTue 12:00 — 17 commitsTue 13:00 — 25 commitsTue 14:00 — 34 commitsTue 15:00 — 29 commitsTue 16:00 — 36 commitsTue 17:00 — 30 commitsTue 18:00 — 31 commitsTue 19:00 — 29 commitsTue 20:00 — 23 commitsTue 21:00 — 27 commitsTue 22:00 — 21 commitsTue 23:00 — 41 commitsWed 0:00 — 55 commitsWed 1:00 — 52 commitsWed 2:00 — 29 commitsWed 3:00 — 20 commitsWed 4:00 — 26 commitsWed 5:00 — 25 commitsWed 6:00 — 20 commitsWed 7:00 — 18 commitsWed 8:00 — 32 commitsWed 9:00 — 19 commitsWed 10:00 — 16 commitsWed 11:00 — 17 commitsWed 12:00 — 17 commitsWed 13:00 — 15 commitsWed 14:00 — 27 commitsWed 15:00 — 26 commitsWed 16:00 — 28 commitsWed 17:00 — 23 commitsWed 18:00 — 25 commitsWed 19:00 — 25 commitsWed 20:00 — 36 commitsWed 21:00 — 29 commitsWed 22:00 — 15 commitsWed 23:00 — 19 commitsThu 0:00 — 20 commitsThu 1:00 — 35 commitsThu 2:00 — 31 commitsThu 3:00 — 25 commitsThu 4:00 — 10 commitsThu 5:00 — 7 commitsThu 6:00 — 4 commitsThu 7:00 — 6 commitsThu 8:00 — 7 commitsThu 9:00 — 8 commitsThu 10:00 — 14 commitsThu 11:00 — 17 commitsThu 12:00 — 4 commitsThu 13:00 — 7 commitsThu 14:00 — 38 commitsThu 15:00 — 32 commitsThu 16:00 — 38 commitsThu 17:00 — 49 commitsThu 18:00 — 27 commitsThu 19:00 — 26 commitsThu 20:00 — 19 commitsThu 21:00 — 35 commitsThu 22:00 — 27 commitsThu 23:00 — 43 commitsFri 0:00 — 33 commitsFri 1:00 — 29 commitsFri 2:00 — 26 commitsFri 3:00 — 28 commitsFri 4:00 — 22 commitsFri 5:00 — 16 commitsFri 6:00 — 28 commitsFri 7:00 — 24 commitsFri 8:00 — 25 commitsFri 9:00 — 18 commitsFri 10:00 — 20 commitsFri 11:00 — 23 commitsFri 12:00 — 26 commitsFri 13:00 — 22 commitsFri 14:00 — 45 commitsFri 15:00 — 37 commitsFri 16:00 — 33 commitsFri 17:00 — 35 commitsFri 18:00 — 32 commitsFri 19:00 — 23 commitsFri 20:00 — 32 commitsFri 21:00 — 22 commitsFri 22:00 — 28 commitsFri 23:00 — 31 commitsSat 0:00 — 18 commitsSat 1:00 — 28 commitsSat 2:00 — 22 commitsSat 3:00 — 13 commitsSat 4:00 — 15 commitsSat 5:00 — 15 commitsSat 6:00 — 14 commitsSat 7:00 — 13 commitsSat 8:00 — 17 commitsSat 9:00 — 16 commitsSat 10:00 — 19 commitsSat 11:00 — 25 commitsSat 12:00 — 24 commitsSat 13:00 — 29 commitsSat 14:00 — 36 commitsSat 15:00 — 31 commitsSat 16:00 — 32 commitsSat 17:00 — 44 commitsSat 18:00 — 49 commitsSat 19:00 — 44 commitsSat 20:00 — 54 commitsSat 21:00 — 52 commitsSat 22:00 — 47 commitsSat 23:00 — 39 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.
DateListRankStars gained
Sep 10, 2026monthly#16+3,880
Sep 9, 2026monthly#15+3,835
Sep 8, 2026monthly#14+3,715
Sep 7, 2026monthly#14+3,647
Sep 6, 2026monthly#14+3,614
Sep 5, 2026monthly#14+3,587
Sep 4, 2026monthly#14+3,545
Sep 3, 2026weekly#14+1,285
Sep 3, 2026monthly#10+3,579
Sep 2, 2026weekly#14+1,285
Sep 1, 2026weekly#14+1,697
Aug 31, 2026weekly#6+1,973
Aug 30, 2026weekly#5+1,876
Aug 29, 2026weekly#6+1,918
Aug 28, 2026weekly#6+1,978
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