Multica v0.3.24

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 v0.3.24 CLI - Software Mirrors

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multica-cli-0.3.24-macOS-amd64.tar.gz | 5.39 MB

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multica-cli-0.3.24-macOS-arm64.tar.gz | 4.97 MB

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multica-cli-0.3.24-linux-amd64.tar.gz | 5.31 MB

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multica-cli-0.3.24-windows-amd64.zip | 5.47 MB

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multica-cli-0.3.24-windows-arm64.zip | 4.88 MB

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multica-desktop-0.3.24-linux-amd64.deb | 155.63 MB

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multica-desktop-0.3.24-linux-x86_64.AppImage | 221.1 MB

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multica-desktop-0.3.24-linux-x86_64.rpm | 132.84 MB

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multica-desktop-0.3.24-mac-arm64.dmg | 214.27 MB

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multica-desktop-0.3.24-mac-arm64.zip | 204.68 MB

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multica-desktop-0.3.24-windows-arm64.exe | 502.18 MB

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multica-desktop-0.3.24-windows-x64.exe | 164.4 MB

Download Multica v0.3.24 CLI
multica_macOS_amd64.tar.gz | 5.39 MB

Download Multica v0.3.24 CLI
multica_macOS_arm64.tar.gz | 4.97 MB

Download Multica v0.3.24 CLI
multica_linux_amd64.tar.gz | 5.31 MB

Download Multica v0.3.24 CLI
multica_linux_arm64.tar.gz | 4.8 MB

Download Multica v0.3.24 CLI
multica_windows_amd64.zip | 5.47 MB

Download Multica v0.3.24 CLI
multica_windows_arm64.zip | 4.88 MB

Multica v0.3.24 Release Notes:

Changelog

  • 1f8f3e80377741bb398497a1bbdcff0db87d36bb Fix Office 365 SMTP auth fallback (#4157)
  • 114a1ffb8fdc48f3b7f2d3cbba5d47d4ac1ef341 Fix: fail fast when Codex app-server exits MUL-2840 (#4228)
  • d26cac0008342bcc60b809e0288565c72601e770 Guard issue icons against unknown values (#4206)
  • 1f5cb51d4e713d5bf7f2795205103dc6ccd5c0ba MUL-3284: Web UI + CLI (custom runtime PR3) (#4177)
  • 32dac3dd577c2a87b6381b7a985aed835e375b96 MUL-3284: runtime_profile schema (custom runtime PR1) (#4140)
  • 52e76e7b23e9b93a28bfbea9a36bc47aed4aa641 MUL-3284: server API + daemon (custom runtime PR2) (#4149)
  • acb1c3fb64b23b3ebac969b0babc391f0c7dd118 MUL-3331: dedupe/throttle client failure telemetry (#4231)
  • 6bb8cac9ea197bfbb6c16ba1984d561cbec9872f MUL-3332: daemon picks up new custom runtime profiles without restart (#4225)
  • 6e010320f880ff435ca8361c19baef9de83213d8 MUL-3332: prioritize custom runtime profiles (#4229)
  • eb6dffdbc6fac93f810f910b2d0415b23ad6fb6c MUL-3341: clear incompatible model on runtime switch
  • 23eba2407697d8ce0dbd680781884ad6f8178a4b MUL-3363: add 2026-06-17 changelog entry (#4248)
  • 77ac17ef498caf01ba4d588b1e3c031e06bea930 Make custom runtimes appear immediately (#4234)
  • c5eb77853229c4a083f96b7d99eeefcbad04d119 Revert "fix: keep runtime provider arbiter during profile rollout (#4251)" (#4258)
  • 6f2e9aa7a8e829e99e4b7e8cee6923f7111b004a feat(cli): add --thinking-level to agent create and update (#4170) (#4207)
  • 59263df748bf037a1f32b20ac4662c08f2a52724 feat(issues): unify trigger chip copy to will-start phrasing (#4215)
  • 3077810049a616abc1378fdd79c74a342ab1ecaa fix(db): clean pending check suites on workspace delete (#4252)
  • 64ce459e303ae426df4c596f6868bee5bff3ffd6 fix(github): preserve early installation webhook metadata (#4193)
  • 41586f14997aefdb453446e8ac25b1eba48c6aaa fix(github): surface in-flight CI on PR cards (MUL-2392) (#2887)
  • 0f36c888559c3902252222763fe82e26b4ee0d68 fix(markdown): don't auto-link bare filenames as external URLs (#4245)
  • af146b6dc7588a7be6e0d16bd998cf7a70312dde fix(runtimes): re-enable Delete affordance for owners on self-healing runtimes (MUL-3352) (#4240)
  • 3030c803bfcad359df748afe4ac498b130c894b8 fix(scripts): fix version comparison to prevent unnecessary CLI upgrades (#4227)
  • a08281a1b28738c450ce01f86f6d6c9d75445099 fix: keep runtime provider arbiter during profile rollout (#4251)
  • 5a3324e886c565aa40e4861e9ade6d99b94999b1 refactor(runtimes): trim redundant copy in custom runtimes dialog (MUL-3367) (#4254)
  • c27d35b7fe183754861f90d0393720ac9b6b382c style(runtimes): unify header action buttons to match Add a computer (MUL-3368) (#4253)

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 v0.3.24
Free
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Software Informations:
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Operating System:
Windows / macOS / Linux
Date Added:
2026-06-17T11:02:02.457Z
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