Maka has built-in support for the web search feature in the DeepSeek API — https://github.com/maka-agent/maka-agent/pull/2152… The approach is to declare a web_search tool in the API request parameters and directly use the search capability executed on the API side. When using the DeepSeek model, there’s no need to integrate a third-party search engine! Maka will be one of the best Harnesses for DeepSeek/GLM/Kimi adaptation! It already is on various benchmarks!

maka-agent/maka-agent

Source: https://github.com/maka-agent/maka-agent

Maka CI (https://github.com/Maka-Agent/maka-agent/actions/workflows/ci.yml)

License docs

Maka — Your work. Your agent.

A local-first Agent workspace built for real work.

Maka does more than answer questions. With controlled permissions, it can inspect projects, execute tools, produce artifacts, and preserve model messages, tool calls, and durable-task progress as recoverable execution facts. The same Runtime is available through the desktop app, terminal TUI, non-interactive CLI, and Headless runner.

Maka is under active development. The macOS Apple Silicon desktop build is an early public release; data formats, CLI commands, and experimental capabilities may still change.

Why Maka

• Local-first instead of hosted-first: sessions, settings, and run records stay on your machine by default. You choose the model connection: cloud API, local model, or compatible gateway.
• Log is the Runtime: model messages, Tool Calls, Tool Results, and termination facts enter Runtime Event Log. Sessions, UI, model context, and recovery are projections over that log.
• Context is not history: Tool Result pruning and LLM Compaction change what the next inference sees without treating recorded evidence as disposable context.
• A task may outlive a Turn: Headless uses TaskRun, Task Event Log, budgets, and continuation to advance interruptible and inspectable durable work.
• Feedback is not fact authority: Self-check may produce evidence and one bounded repair opportunity, but “I checked it” does not become a system fact.

Read Maka Backend Architecture for the complete design.

Surfaces

Current capabilities

Agent Runtime

• Multiple model connections, streaming output, thinking, usage accounting, and provider-error normalization;
• Local tools including Read, Write, Edit, Bash, Glob, and Grep;
• Tool schema validation, dynamic availability, permission policy, watchdogs, abort, and error classification;
• Runtime Event Log, AgentRun ledger, startup recovery, Turn Evidence, active Tool Result pruning, and history compaction.

Desktop workspace

• Create, archive, search, rename, retry, regenerate, and branch sessions from a Turn;
• Artifact lists and previews, workspace instructions, model settings, and permission settings;
• Local memory, web search, and bot entry points;
• Integrations are configured independently, and not every experimental entry is available by default.

Durable tasks and evolution

• Append-only Task Event Log and TaskRun projection;
• Budgets, permission pauses, continuation, result export, and failed-task retry;
• Plan-first, source-guarded, and attempt-bounded Heavy-task Self-check;
• AHE target protocol and evidence export; complete automatic self-iteration remains an external or experimental workflow.

Quick start

Download Desktop for macOS

The signed and notarized Desktop app is available from GitHub Releases (https://github.com/Maka-Agent/maka-agent/releases/latest) for Apple Silicon Macs only (arm64).

1. Download Maka--mac-arm64.dmg;
2. Open the DMG and drag Maka to Applications;
3. Install ripgrep with brew install ripgrep to enable Runtime’s Grep tool;
4. Launch Maka and configure your own model connection under Settings → Models.

Computer Use is not included in this first public build. Intel Macs, Windows, and Linux packages are not supported yet.

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

sh git clone https://github.com/Maka-Agent/maka-agent.git cd maka-agent npm ci npm run dev

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

sh npm run dev:full

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

sh 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

Build the workspaces first:

sh npm run build

Then start the TUI or run one Turn:

sh npm --workspace maka-agent exec -- maka npm --workspace maka-agent exec -- maka run "Summarize this repository and identify its most important risk" npm --workspace maka-agent exec -- maka run --graph "Implement two independent slices, integrate them, then review the result" npm --workspace maka-agent exec -- maka --help

The TUI also accepts /graph on, /graph off, and /graph . 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 CLI reads the same model connections and workspace configuration written by Desktop. See packages/headless/README.md for Headless commands and its trust posture.

Architecture

The backend spine is:

text Desktop / TUI / Headless ↓ SessionManager → AgentRun → Model + Tool Runtime ↓ Runtime Event Log → Context / Session / UI projections ↓ Task Event Log → TaskRun → Self-check / AHE evidence

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

Repository layout

text 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/runtime/ AgentRun, model adapters, tools, context, and recovery packages/headless/ TaskRun, Autonomous Loop, Self-check, eval, and AHE 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 security boundary

Maka stores workspace data under Electron userData by default:

text /workspaces/default/ runtime.sqlite llm-connections.json credentials.json settings.json artifacts/

Current boundaries that matter:

• Sessions, messages, execution ledgers, workflows, usage, Automations, Daily Review, and Headless TaskRuns live in runtime.sqlite;
• Runtime credentials such as API keys, bot tokens, and proxy passwords currently live in local plaintext credentials.json, behind the OS account boundary, with POSIX directory mode 0700 and file mode 0600 enforced;
• Subscription OAuth tokens (Claude, Codex, GitHub Copilot, xAI, and the Antigravity preview) live in the same credentials.json — the single authority for desktop, TUI, and headless. Pre-existing Electron safeStorage credential/token files are not imported; affected users must re-authenticate;
• Renderer does not receive plaintext credentials. File writes, Shell, and dangerous tool calls pass through the permission engine;
• Headless real-model evaluation fails closed by default and requires an explicit external isolation boundary.

Read SECURITY.md for security reporting and policy, and docs/README.md for current privacy and sandbox contracts.

Runtime storage and recovery

runtime.sqlite is the sole operational authority. It owns RuntimeEvents, session metadata and message history, Agent Graph control, core execution state, workflow state, usage and pricing, Artifact metadata, Automations, Daily Review, and Headless TaskRuns. Artifact payload bytes remain regular files under artifacts/; connections, credentials, settings, MCP configuration, skills, and device identity remain configuration files.

This storage generation does not import earlier File/JSONL authorities. On upgrade, legacy session titles may still be discoverable through current metadata, but conversation history that exists only in legacy transcript files is not copied into session_messages and opens as an empty thread. Likewise, pre-version or safeStorage-encrypted credential/token files are not migrated; users with only those copies must re-authenticate. This data-loss boundary is intentional for this release and must be considered before upgrading an existing workspace.

Full operational backup uses the database owner’s online SQLite backup API and copies canonical Artifact payloads under the Artifact writer lock. Its manifest binds every file by size and SHA-256. Validation checks the standalone SQLite snapshot’s integrity, foreign keys, schema registry and required tables, decodes canonical session-message and Artifact records, and verifies Artifact payload sizes against SQLite metadata before restore. Backup and restore use owner-only file modes, file and directory synchronization, staging, and atomic publication.

Headless trajectory hydration now consumes a frozen selected-session export from that SQLite Artifact authority. The cell publishes trajectory-state only when RuntimeEvents reference image Artifacts; Harbor downloads its standalone runtime.sqlite first and then only the payloads referenced by the validated snapshot. It does not copy a live WAL or fall back to artifacts/metadata.jsonl. Missing, corrupt, unsupported, or mismatched evidence fails closed to a summary trajectory instead of mixing authorities.

Runtime continuation remains opt-in:

• MAKA_RUNTIME_SAFE_BOUNDARY_RESUME=1 enables the Desktop interrupted-turn Safe resume action, CLI/TUI /resume, and Desktop startup auto-resume. These paths may call the configured model provider and consume tokens. Enable the flag only when that behavior is explicitly desired.

Phase 2 provides the durable write-side boundary and fail-closed safe-boundary continuation. Phase 3 reconciliation for indeterminate tool side effects is not implemented yet; ambiguous tool outcomes remain parked rather than retried.

Development and verification

Common repository-level commands:

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

Run one workspace in isolation:

sh npm --workspace @maka/runtime test npm --workspace @maka/headless test npm --workspace @maka/desktop test

Use the following commands to update packages/core/src/model-metadata.generated.ts from models.dev and run the focused tests. Keep access-path-specific overrides in model-metadata.ts; do not edit the generated file by hand.

sh npm run sync:model-metadata npm run test:scripts npm --workspace @maka/core test

Desktop real-window and visual verification:

sh 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

• Documentation index and authority map
• Backend architecture
• Product design
• Security policy

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.