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Sidekick Review: A Free, Native macOS Local AI Chat App

·10 min readBy Hans Kuepper · Founder of PromptQuorum · Discovery engine for open-weight & open-source AI

Sidekick is a free, open-source, native macOS app that lets you chat with a local LLM that can respond using information from your own files, folders, and websites, without installing any other software. Created by developer John Bean (johnbean393) and released under the MIT license, Sidekick runs entirely on Apple Silicon Macs through a built-in llama.cpp engine, and can also connect to cloud providers such as OpenAI, Anthropic, Google AI Studio, DeepSeek, and Groq through their APIs.

Key Takeaways

  • Sidekick (github.com/johnbean393/Sidekick) is a free, open-source, native macOS app — not a cross-platform Electron app
  • Created by developer John Bean (GitHub handle johnbean393)
  • MIT licensed, confirmed via the repository's LICENSE file
  • Requires an Apple Silicon (M-series) Mac — this review found no Intel Mac, Windows, or Linux build
  • Runs local models through a built-in llama.cpp engine, with retrieval-augmented generation over your own files, folders, and websites via customizable "Experts"
  • Can optionally connect to cloud providers — OpenAI, Anthropic, Google AI Studio, DeepSeek, Groq — through OpenAI-compatible API connections
  • Over 3,300 GitHub stars as of this review, per GitHub API

📍 In One Sentence

Sidekick is a free, open-source (MIT), native macOS app for Apple Silicon Macs that chats with a local LLM through a built-in llama.cpp engine and can answer questions using your own files, folders, and websites, with over 3,300 GitHub stars.

💬 In Plain Terms

Sidekick is a Mac app you download, install, and run without a terminal or Python setup. It downloads an AI model to your own computer and lets you point it at specific folders, files, or web pages so it can answer questions about them — no cloud account or subscription needed, though you can optionally add a cloud API key later.

📌Note: This review is the deep-dive companion to Sidekick's entry in the Local LLM Software Directory — see that page for how Sidekick compares at a glance to dozens of other local AI tools. It is based on Sidekick's own GitHub repository, README, and setup guide, not hands-on benchmarking by PromptQuorum.

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Sidekick (github.com/johnbean393/Sidekick) is a free, open-source, native macOS application that chats with a local LLM and can pull in information from your own files, folders, and websites, with no other software required. It is built on llama.cpp for local inference and is designed specifically for Apple Silicon Macs, with over 3,300 GitHub stars. This review covers what Sidekick actually does, how to install it, and who it fits.

What Is Sidekick?

Sidekick is a native macOS chat application that runs a local LLM on your own Mac and can pull relevant information from your own files, folders, and websites into its answers, without needing any other software installed. Its own GitHub description states it lets users "chat with a local LLM that can respond with information from files, folders and websites on your Mac."

  • Product type: a native macOS desktop application, not a browser app, CLI tool, or IDE extension
  • Creator: developer John Bean, GitHub handle johnbean393
  • Repository: github.com/johnbean393/Sidekick
  • License: MIT, confirmed via the repository's own LICENSE file
  • Platform: Apple Silicon (M-series) Macs only, per the project's own setup guide — this review found no Intel Mac, Windows, or Linux build
  • Scale: over 3,300 GitHub stars as of this review, per GitHub API

What Does Sidekick Actually Do?

Sidekick runs a local LLM on your Mac and layers retrieval-augmented generation, tool use, and a few other features on top of it, all built into one native app.

  • Local-first chat — runs GGUF models locally through a built-in llama.cpp engine, so conversations can happen fully offline once a model is downloaded
  • "Experts" (retrieval-augmented generation) — point Sidekick at specific files, folders, or websites, and it retrieves relevant passages into its answers, entirely on-device
  • Cloud provider connections — optionally add your own API key for OpenAI, Anthropic, Google AI Studio, DeepSeek, Groq, or other OpenAI-compatible endpoints, to use cloud models alongside local ones
  • Function calling — Sidekick's own documentation describes sequential tool execution, letting the model call functions to perform calculations or actions as part of a response
  • Deep Research — a multi-step research agent that Sidekick's own project description says can synthesize information across 50–80 webpages for a single query
  • Memory — retains information about the user between separate conversations, per the project's own feature list
  • Canvas editor — a built-in editor for creating and selectively editing websites and code, rather than only receiving code in chat form
  • Image generation — automatic detection and image generation via CoreML on macOS 15.2 and later, per the project's documentation

Usage Examples: Three Ways to Use Sidekick

These are concrete workflows built from Sidekick's documented features above — not hypothetical use cases.

Chat with a local model fully offline

Install Sidekick, download a GGUF model sized for your Mac's memory (Sidekick's own documentation notes support for modern models like Qwen-family releases), and start chatting. Once the model is downloaded, you can disconnect from the internet entirely — the conversation runs through Sidekick's built-in llama.cpp engine, so nothing leaves your Mac.

Create an "Expert" over a folder of documents

Point Sidekick's retrieval-augmented generation feature at a specific folder — for example, a set of PDFs or notes — and ask questions about their contents. Sidekick retrieves relevant passages on-device and includes them in the model's answer, without uploading the documents anywhere.

Add a cloud API key for harder tasks

In Sidekick's settings, add your own OpenAI, Anthropic, Google AI Studio, DeepSeek, or Groq API key. This makes a cloud model available in the same app alongside your local one, so you can switch to a larger cloud model for a more demanding task without leaving Sidekick.

Platform, Pricing, and Licensing

Platform

What Sidekick states:
A native macOS app for Apple Silicon (M-series) Macs only, per the project's own setup guide — no Intel Mac, Windows, or Linux build.

Cost

What Sidekick states:
Free and open source. Cloud provider connections are optional — you pay that provider directly if you add an API key; Sidekick itself has no paid tier.

Licensing

What Sidekick states:
MIT license, confirmed via the repository's own LICENSE file.

Requirements

What Sidekick states:
Apple Silicon Mac with at least 8 GB RAM; image generation additionally requires macOS 15.2 or later, per the project's documentation.

Verify current requirements and licensing directly on github.com/johnbean393/Sidekick before relying on this table for a compliance or purchasing decision.

Who Should Use Sidekick?

Sidekick fits Mac owners on Apple Silicon who want a native, no-terminal way to chat with a local model over their own files without installing any other software.

Use Sidekick if you

  • Own an Apple Silicon Mac and want a native app rather than a cross-platform Electron app
  • Want to chat with a local model over your own files, folders, or websites without uploading them anywhere
  • Prefer a one-step Homebrew or direct-download install over a terminal-based or Python-based setup
  • Want the option to add a cloud provider API key later without switching apps
  • Are interested in built-in extras like a canvas editor, function calling, or a multi-step research agent alongside basic chat

Look elsewhere if you

  • Use an Intel Mac, Windows, or Linux machine — Sidekick has no build for any of those
  • Need a mobile app — this review found no iOS or Android version of Sidekick
  • Want a tool backed by a company with dedicated support staff, rather than an independent developer's project
  • Need enterprise features like team accounts, centralized admin controls, or an SLA

What Sidekick Is Not Good For

Sidekick is not a fit if you are not on Apple Silicon, or if you need a mobile app or enterprise-grade support.

  • Not for Intel Macs, Windows, or Linux — this review found no build for any platform other than Apple Silicon macOS
  • Not a mobile app — there is no iOS or Android version documented in the repository
  • Not backed by a company this review could verify — treat Sidekick as an independently maintained, community-supported project rather than a venture-backed product with a guaranteed long-term roadmap
  • Not a fixed-cost tool if you add cloud providers — connecting OpenAI, Anthropic, or another API key means your costs scale with that provider's own pricing, separate from Sidekick itself
  • Not built for enterprise deployment — this review found no team-account, centralized-admin, or SLA offering

Common Mistakes When Evaluating Sidekick

Most confusion about Sidekick comes from conflating it with unrelated same-named projects, or assuming it supports hardware it does not.

Mistake 1: Confusing Sidekick with an unrelated project of the same name

"Sidekick" is a common open-source project name. Verify you are looking at github.com/johnbean393/Sidekick specifically — not one of several other, unrelated "sidekick" repositories — before installing.

Mistake 2: Assuming Sidekick runs on Intel Macs or other operating systems

Sidekick is built specifically for Apple Silicon (M-series) Macs, per its own setup guide. This review found no Intel Mac, Windows, or Linux build — check the current requirements on GitHub before assuming compatibility with your hardware.

Mistake 3: Assuming all features require a cloud connection

Core chat and the retrieval-augmented "Experts" feature run entirely on-device through the built-in llama.cpp engine. Cloud provider connections are opt-in, for when you want a larger model than your Mac can run locally.

Mistake 4: Assuming Sidekick is backed by a funded company

This review found no evidence of a funding round or commercial company behind Sidekick — treat it as an independently maintained open-source project by developer John Bean, unless you find a specific, dated source stating otherwise.

Competitors and Alternatives

Within native, local-first Mac chat apps, Sidekick is most directly comparable to Enchanted and BoltAI, plus Msty for a cross-platform alternative and Khoj for a document-focused competitor with a similar retrieval-augmented approach.

BoltAI

Best known for:
Native macOS AI chat app with system-wide shortcuts and multiple provider support
Link:
BoltAI Review
Articles about BoltAI (2)

Also mentioned in:

This is not an exhaustive list of local chat apps — see the Local LLM Software Directory for the full, regularly updated catalog, including Sidekick's own directory entry.

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Frequently Asked Questions

What is Sidekick?

Sidekick (github.com/johnbean393/Sidekick) is a free, open-source (MIT), native macOS app that chats with a local LLM and can answer questions using your own files, folders, and websites.

Is Sidekick free?

Yes, Sidekick itself is free and open source under the MIT license. Connecting an optional cloud provider (OpenAI, Anthropic, etc.) costs whatever that provider charges you directly; Sidekick does not add a fee on top.

How do I install Sidekick?

Per the project's own documentation, run brew install --cask arcadi4/tap/sidekick via Homebrew, or use the direct download linked from Sidekick's GitHub repository. Both require an Apple Silicon Mac.

Does Sidekick work on Intel Macs, Windows, or Linux?

No. This review found no Intel Mac, Windows, or Linux build — Sidekick is built specifically for Apple Silicon (M-series) Macs.

Does Sidekick require an internet connection?

No, not for core chat and file/folder retrieval — once a model is downloaded, Sidekick runs entirely on-device through its built-in llama.cpp engine. An internet connection is only needed if you add an optional cloud provider API key.

What local models does Sidekick support?

Sidekick runs GGUF models through its built-in llama.cpp engine, including modern model families such as Qwen, per the project's own documentation. Check the GitHub repository for the current list of tested models.

Who created Sidekick?

Developer John Bean (GitHub handle johnbean393) created and maintains Sidekick as an independent open-source project.

Can Sidekick answer questions about my own files?

Yes, through its "Experts" feature — retrieval-augmented generation over files, folders, or websites you point it at, processed entirely on-device.

What is Sidekick's minimum hardware requirement?

An Apple Silicon (M-series) Mac with at least 8 GB of RAM, per the project's own setup guide. Which specific local models run comfortably depends on that model's own size relative to your Mac's memory.

Has PromptQuorum independently tested Sidekick's feature claims?

This review is based on Sidekick's own GitHub repository, README, and setup guide, rather than hands-on benchmarking by PromptQuorum.

Sources

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