Multica v0.4.44

Multica is an open-source platform designed to manage and orchestrate AI agents within development workflows. Instead of running a single AI assistant, it allows multiple agents to collaborate, execute tasks, and share knowledge across projects.

It essentially acts like a control center where:

  • AI agents are assigned tasks

  • Progress is tracked in real time

  • Outputs and skills are reused across workflows

Multica currently supports Claude Code, Codex, OpenClaw, and OpenCode out of the box. The daemon auto-detects whichever CLIs you have installed. Since it’s open source, you can also add your own backends.

Download Multica v0.4.44 - Software Mirrors

Multica v0.4.44 for Windows

multica-cli-0.4.44-windows-amd64.zip | 6.98 MB

multica-cli-0.4.44-windows-arm64.zip | 6.21 MB

multica-desktop-0.4.44-windows-arm64.exe | 169.48 MB

multica-desktop-0.4.44-windows-x64.exe | 168.21 MB

multica_windows_amd64.zip | 6.98 MB

multica_windows_arm64.zip | 6.21 MB

Multica v0.4.44 for macOS

multica-cli-0.4.44-darwin-amd64.tar.gz | 6.9 MB

multica-cli-0.4.44-darwin-arm64.tar.gz | 6.36 MB

multica_darwin_amd64.tar.gz | 6.9 MB

multica_darwin_arm64.tar.gz | 6.36 MB

Multica v0.4.44 for Linux

multica-cli-0.4.44-linux-amd64.tar.gz | 6.77 MB

multica-cli-0.4.44-linux-arm64.tar.gz | 6.1 MB

multica-desktop-0.4.44-linux-aarch64.rpm | 130.48 MB

multica-desktop-0.4.44-linux-amd64.deb | 159.58 MB

multica-desktop-0.4.44-linux-arm64.AppImage | 225.11 MB

multica-desktop-0.4.44-linux-arm64.deb | 153.5 MB

multica-desktop-0.4.44-linux-x86_64.AppImage | 225.64 MB

multica-desktop-0.4.44-linux-x86_64.rpm | 136.46 MB

multica_linux_amd64.tar.gz | 6.77 MB

multica_linux_arm64.tar.gz | 6.1 MB

Multica v0.4.44 Release Notes:

Changelog

  • 023c349f5f8de922437dba07449f5f1c95af26d4 MUL-7072 chore(db): drop the reference_only column (#8253)
  • 8bf525eb2dde0e4e97174bc21ecbc6ff11fc998a MUL-7106 feat(dingtalk): add contextual replies and task lifecycle reactions (#8125)
  • 7ebe0bf58d99238ccf830c7ed1aa658d4f5807d0 MUL-7213: feat(server): Triage has no executor (#8373)
  • 3551e72e76d2c276e550b668303646d1280fb1e2 MUL-7232 feat(daemon): add dsh desktop(self-hosted) support (#8237)
  • dee1ed6bf956917bb5aa669b24da7c52cae3acfa MUL-7236: add anonymous self-host telemetry (#8252)
  • 7dafc0cd625425b91e698a5f6e555a37a1846e68 MUL-7240: Unify issue lifecycle into four stored categories (#8261)
  • 686957e74346e55dcd3522ff9d475a3d6bd4f2c1 MUL-7271: test(server): cut slow Go test time further (follow-up to #8295) (#8318)
  • 8bf3046f2203966c8a9890d341c71fa4a725129c MUL-7275: fix(skills): normalize Windows archive entry paths (#8297)
  • a9e82c79739446111b8ca9acbb256f584072d20d MUL-7282: fix(comments): delete only the selected comment and keep its replies (#8323)
  • 27d0529faf696f4777903f81e68a48d51052523b MUL-7319 fix(wecom): a completion of whitespace is not a message (#8347)
  • b8d03bc3f498fbba2dc251f2b62b731a50b6c220 MUL-7326 fix(service): coalesce duplicate EnqueueTaskForIssue on the assignee path (#5914) (#6304)
  • 49cd223046a0382a4fca534331f4bdb92488abd0 MUL-7339: fix(comments): stop rendering a placeholder for a deleted reply (#8371)
  • 5d7877287c1e94d412b61905aaec77c10da7e16a MUL-7340 fix(lark): share bind-session state across replicas so the QR survives the first status poll (#8376)
  • 361edd90a1aff8c42e4f990edf830c58cd897b85 MUL-7342: index chat session delete lookups (#8375)
  • e0b1f1cf1009aa1742dc9b3934eaf9dbad5a8d2f MUL-7355 fix(claude): deduplicate fallback usage by response ID (#8382)
  • b62cce56dab6f75e83c7743904dcd02f0dfa7e91 MUL-7359 perf(runtime): avoid echoing final comment bodies (#8390)
  • f0317cd0074b766797871be7f5e8b15c8d1f5ee2 MUL-7373 fix(docker): upgrade Alpine OpenSSL packages in web image (#8414)
  • d665f0ac604225ac94ca9f208c5b047052879133 MUL-7379 docs: retranslate the issue status model and correct category-wide behavior claims (#8438)
  • ff60b2f25a0233309ba49d02a5f4d45540332181 MUL-7379 fix: restore per-status sort order and the delegated handoff signal (#8435)
  • 8d294d0ab2578704f2af91de91748f8e079e5ced Revert "docs(changelog): add v0.4.44 release entry (2026-09-14) (MUL-7356) (#…" (#8403)
  • 1a660e6c15128b3162552337148e5285a42b91be docs(changelog): add v0.4.44 release entry (2026-09-14) (MUL-7356) (#8396)
  • 93b4c3815057221d44decc05f68e16f80e841e1d docs(changelog): add v0.4.44 release entry (2026-09-15) (MUL-7400) (#8446)
  • 02a8ff3e95ed3725d1a7d3615642f80f35001d4c feat(maintenance): add resumable internal backfill API (MUL-7365) (#8436)
  • 8908fcfbc43d18fc515dec747a100fecccc33556 feat(server): reserve the triage status key (MUL-7212) (#8298)
  • f639d35f44eeedd30046046c1c29a915199d379d fix(agents): MUL-7383 exclude cancelled runs from success metrics (#8424)
  • fe4d6a49c341980a22a5d3746932dfe7782411c9 fix(autopilot): show last run status in list (#8354)
  • c26da76c42c8aaca846986023012daa988e5888e fix(codebuddy): deduplicate fallback usage by response ID (#8395)
  • cf52ba33ccf97f756de9e6b9d364fc0a57dc5260 fix(codex): MUL-7374 avoid double-counting reasoning output tokens (#8416)
  • a00ebbb952f51e729d1d9ab61095c39167dc91ca fix(codex): MUL-7381 synchronize codex thread ID access (#8428)
  • a1922018d0c8aa992b1c542a6a0cc884e4dca843 fix(daemon): discover Hermes local skills from the home tasks run against (#8327)
  • aac85ab263a6080d577fa62f02c08cf61c9fd7d6 fix(daemon): preserve issue status catalog wire compatibility (#8378)
  • 24fecdd91b2a5e3da80e56b8918d9a0a57ab37c7 fix(db): restore unique migration prefixes (#8372)
  • 7d9613bd2c446d1d2815dff28ab571a397324ddd fix(issues): show content previews in inline agent logs (#8408)
  • 408bf2b270ecbdeb306c76a71ec30b9f7e812cdb fix(lark): honor the device-flow expires_in so the bind QR keeps its full 1h window (MUL-7340) (#8370)
  • dd785a5cd818a38d48b015ca9a203aba911f0931 fix(migrations): add the Triage column CHECK without scanning the issue table (#8449)
  • ee1ea34744b37248fa80c152973b07939279bcf9 fix(migrations): renumber the Triage validate migration to 489 (#8452)
  • c4c8bab56c38911feae7fb56ae7e5fc171c7a69d fix(opencode): include separate reasoning in output usage (#8431)
  • d77a1c5ea75a5e9e89dcff080024d740fb723c2a fix(prompts): remove status wire details from operational guidance (#8401)
  • 20f20d6bc769ac9550e3e8ce0431f9bee34e3617 fix(qwen): exclude cache reads from plain input usage (#8440)
  • 1b3137a00d61f0911f8e45d85e92ae9cd78d5146 fix(server): MUL-7364 decide issue GC and recovery prefilter on lifecycle category (#8405)
  • 95629c6d5b8289467f7335649aa9c9adeb9746fa fix(sidebar): align help after dismissing Discord link (#8437)
  • 9d18186e6e8cfa168d6053d33d652e86fadfc12b fix(status): MUL-7365 expand category compatibility before backfill (#8407)
  • dddbb033637d008298927be2c37867426a51a720 fix(tasks): prevent delegated failure recovery starvation (#8406)
  • 2295be9271d85928db5f742cda49324b3a510807 fix(test): widen the codex retry handshake budget so CI stops flaking (#8386)
  • a3318b68deb5437d071f4bdb09a9f1902e7e3eef fix(views): move issue refresh feedback into page title icons (#8430)
  • c7f259c70a60bff30011c403fada79ab382f608a revert(server): withdraw the reserved triage status key (#8450)
  • 8b7a4fb68acd42258de130c1b317ff2d1287aeed test(daemon): isolate local skill homes on Windows (#8338)


Key Features

1. AI Agents as Teammates

Multica treats AI agents like real contributors. You can assign tasks, monitor progress, and manage their work similar to human developers.


2. Multi-Agent Orchestration

Instead of relying on a single AI model, Multica coordinates multiple agents working together on complex tasks, improving efficiency and scalability.


3. Skill Reuse and Compounding

One of its most innovative features is skill accumulation. Agents can reuse previously learned solutions, reducing redundancy and improving performance over time.


4. Real-Time Workflow Tracking

You get a unified dashboard where you can:

  • Track task progress

  • Monitor agent activity

  • Identify blockers and results

This makes it suitable for structured development environments.


5. CLI and Web Interface

Multica provides both:

  • A command-line interface for developers

  • A web UI for managing workflows and agents

It supports local and cloud-based environments, offering flexibility in deployment.


6. Open Source and Flexible

Being open source, Multica allows:

  • Full customization

  • Self-hosting

  • Integration with different AI models and tools

This makes it appealing for teams that want control over their AI infrastructure.


Performance and Use Cases

Multica is designed for advanced workflows rather than casual use. It performs best in environments where multiple AI agents are needed to collaborate.

Typical use cases include:

  • AI-assisted software development

  • Automation pipelines

  • Multi-step research and analysis

  • DevOps and engineering workflows

Its ability to coordinate agents makes it especially useful for complex tasks that go beyond simple prompts.

Quick Install

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash

Installs the Multica CLI on macOS and Linux. Works with Homebrew or downloads the binary directly.

Windows (PowerShell):

irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex

Then configure, authenticate, and start the daemon in one command:

multica setup          # Connect to Multica Cloud, log in, start daemon

Self-hosting? Add --with-server to deploy a full Multica server on your machine:

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash -s -- --with-server
multica setup self-host

Requires Docker. See the Self-Hosting Guide for details.


Getting Started

1. Set up and start the daemon

multica setup           # Configure, authenticate, and start the daemon

The daemon runs in the background and auto-detects agent CLIs (claude, codex, openclaw, opencode) on your PATH.

2. Verify your runtime

Open your workspace in the Multica web app. Navigate to Settings → Runtimes — you should see your machine listed as an active Runtime.

What is a Runtime? A Runtime is a compute environment that can execute agent tasks. It can be your local machine (via the daemon) or a cloud instance. Each runtime reports which agent CLIs are available, so Multica knows where to route work.

3. Create an agent

Go to Settings → Agents and click New Agent. Pick the runtime you just connected and choose a provider (Claude Code, Codex, OpenClaw, or OpenCode). Give your agent a name — this is how it will appear on the board, in comments, and in assignments.

4. Assign your first task

Create an issue from the board (or via multica issue create), then assign it to your new agent. The agent will automatically pick up the task, execute it on your runtime, and report progress — just like a human teammate.


User Experience

The concept behind Multica is powerful, but it comes with complexity.

  • Requires understanding of AI agents and workflows

  • Setup may involve configuring runtimes and integrations

  • More suited for developers than beginners

However, once configured, it provides a highly structured and scalable system.


Pros and Cons

Pros

  • Open source and highly customizable

  • Supports multi-agent collaboration

  • Reusable skill system improves efficiency

  • Real-time workflow tracking

  • Flexible deployment options

Cons

  • Still early-stage and evolving

  • Setup complexity is high

  • Requires technical knowledge

  • Not suitable for simple AI tasks


Who Should Use Multica

Multica is ideal for:

  • Developers working with AI agents

  • Teams building automated workflows

  • Companies experimenting with agent-based systems

  • Advanced users exploring AI orchestration

It is not designed for casual users who just need a simple chatbot.


Final Verdict

Multica represents the next step in AI tooling, moving from single assistants to collaborative AI systems. While still evolving, it introduces a powerful concept that could shape how teams use AI in development.

Multica is a promising platform for advanced users who want to build scalable, multi-agent AI workflows with full control and flexibility.

If you are exploring multi-agent AI systems or building automated development workflows, Multica is an emerging tool worth paying attention to. It introduces a new way to treat AI agents not just as tools, but as collaborative team members working alongside developers.

Multica v0.4.44
Free
Software Informations:
Developer:

Operating System:
Windows / macOS / Linux
Date Added:
2026-09-15T11:03:57.327Z
Categories:

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