Free open source alternatives for macOS

Browse free and open source software that runs on macOS. Find open-source alternatives, compare features, platforms and pricing, and pick the right macOS tool for you.

Redis Commander

Redis web management tool written in node.js.http://jk.topfreealternative.com/wp-content/uploads/2024/08/1724250300-Xnip2024-08-21_22-22-12.jpg Web-UI to display and edit data within multiple different Redis servers. It can connect to Redis standalone server, Sentinel based setups and Redis Cluster. It has support for the following data types to view, add, update and delete data: Strings Lists Sets Sorted Set Streams (Basic support based on HFXBus project from https://github.com/exocet-engineering/hfx-bus , only view/add/delete data) ReJSON documents (Basic support, only for viewing values of ReJSON type keys)

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Cakebrew

The Mac App for Homebrew. Useful Do most of the usual tasks you need of Homebrew. Including updating and finding problems with the Doctor! Practical & Easy Afraid to use the terminal? Cakebrew supports Homebrew/bundle. Export and import formulae easily!

FreemacOS

Compatibility.work

Compatibility.work is a free, lightweight, and anonymous online tool built for personal entertainment. It lets users explore relationship compatibility through MBTI personality types, zodiac signs, and moon phases. With a simple three-step process, anyone can select two profiles and instantly get an AI-generated breakdown of matches, clashes, and connection dynamics. The platform requires no registration, runs quickly, and focuses on casual, fun insights rather than scientific claims. It’s designed to be easy, approachable, and lighthearted for anyone curious about personality and interpersonal dynamics.

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redis

redis is a free, open-source alternative to Redis Enterprise . This document serves as both a quick start guide to Redis and a detailed resource for building it from source. New to Redis? Start with What is Redis and Getting Started Ready to build from source? Jump to Build Redis from Source Want to contribute? See the Code contributions section and CONTRIBUTING.md Looking for detailed documentation? Navigate to redis.io/docs Table of contents What is Redis? Key use cases Why choose Redis? What is Redis Open Source? Getting started Redis starter projects Using Redis with client libraries Using Redis with redis-cli Using Redis with Redis Insight Redis data types, processing engines, and capabilities Cloud hosted Redis Community Build Redis from source Install dependencies and build Building Redis - flags and general notes Fixing build problems with dependencies or cached build options Fixing problems building 32 bit binaries Allocator Monotonic clock Verbose build Running Redis with TLS Code contributions Redis Trademarks What is Redis? For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine. Key use cases Redis excels in various applications, including: Caching: Supports multiple eviction policies, key expiration, and hash-field expiration. Distributed Session Store: Offers flexible session data modeling (string, JSON, hash). Data Structure Server: Provides low-level data structures (strings, lists, sets, hashes, sorted sets, JSON, etc.) with high-level semantics (counters, queues, leaderboards, rate limiters) and supports transactions & scripting. NoSQL Data Store: Key-value, document, and time series data storage. Search and Query Engine: Indexing for hash/JSON documents, supporting vector search, full-text search, geospatial queries, ranking, and aggregations via Redis Search. Event Store & Message Broker: Implements queues (lists), priority queues (sorted sets), event deduplication (sets), streams, and pub/sub with probabilistic stream processing capabilities. Vector Store for GenAI: Integrates with AI applications (e.g. LangGraph, mem0) for short-term memory, long-term memory, LLM response caching (semantic caching), and retrieval augmented generation (RAG). Real-Time Analytics: Powers personalization, recommendations, fraud detection, and risk assessment. Why choose Redis? Redis is a popular choice for developers worldwide due to its combination of speed, flexibility, and rich feature set. Here's why people choose Redis for: Performance: Because Redis keeps data primarily in memory and uses efficient data structures, it achieves extremely low latency (often sub-millisecond) for both read and write operations. This makes it ideal for applications demanding real-time responsiveness. Flexibility: Redis isn't just a key-value store, it provides native support for a wide range of data structures and capabilities listed in What is Redis? Extensibility: Redis is not limited to the built-in data structures, it has a modules API that makes it possible to extend Redis functionality and rapidly implement new Redis commands Simplicity: Redis has a simple, text-based protocol and well-documented command set Ubiquity: Redis is battle tested in production workloads at a massive scale. There is a good chance you indirectly interact with Redis several times daily Versatility : Redis is the de facto standard for use cases such as: Caching: quickly access frequently used data without needing to query your primary database Session management: read and write user session data without hurting user experience or slowing down every API call Querying, sorting, and analytics: perform deduplication, full text search, and secondary indexing on in-memory data as fast as possible Messaging and interservice communication: job queues, message brokering, pub/sub, and streams for communicating between services Vector operations: Long-term and short-term LLM memory, RAG content retrieval, semantic caching, semantic routing, and vector similarity search In summary, Redis provides a powerful, fast, and flexible toolkit for solving a wide variety of data management challenges. If you want to know more, here is a list of starting points: Introduction to Redis data types The full list of Redis commands Redis for AI Redis documentation What is Redis Open Source? Redis Community Edition (Redis CE) was renamed Redis Open Source with the v8.0 release. Redis Ltd. also offers Redis Software , a self-managed software with additional compliance, reliability, and resiliency for enterprise scaling, and Redis Cloud , a fully managed service integrated with Google Cloud, Azure, and AWS for production-ready apps. Read more about the differences between Redis Open Source and Redis here . Getting started If you want to get up and running with Redis quickly without needing to build from source, use one of the following methods: Redis Cloud Official Redis Docker images (Alpine/Debian) docker run -d -p 6379:6379 redis:latest Redis binary distributions Snap Homebrew RPM Debian Redis quick start guides If you prefer to build Redis from source - see instructions below. Redis starter projects To get started as quickly as possible in your language of choice, use one of the following starter projects: Python (redis-py) C#/.NET (NRedisStack/StackExchange.Redis) Go (go-redis) JavaScript (node-redis) Java/Spring (Jedis) Using Redis with client libraries To connect your application to Redis, you will need a client library. Redis has documented client libraries in most popular languages, with community-supported client libraries in additional languages. Python (redis-py) Python (RedisVL) C#/.NET (NRedisStack/StackExchange.Redis) JavaScript (node-redis) Java (Jedis) Java (Lettuce) Go (go-redis) PHP (Predis) C (hiredis) Full list of client libraries Using Redis with redis-cli redis-cli is Redis' command line interface. It is available as part of all the binary distributions and when you build Redis from source. You can start a redis-server instance, and then, in another terminal try the following: cd src ./redis-cli redis> ping PONG redis> set foo bar OK redis> get foo "bar" redis> incr mycounter (integer) 1 redis> incr mycounter (integer) 2 redis> Using Redis with Redis Insight For a more visual and user-friendly experience, use Redis Insight - a tool that lets you explore data, design, develop, and optimize your applications while also serving as a platform for Redis education and onboarding. Redis Insight integrates Redis Copilot , a natural language AI assistant that improves the experience when working with data and commands. Redis Insight documentation Redis Insight GitHub repository Redis data types, processing engines, and capabilities Redis provides a variety of data types, processing engines, and capabilities to support a wide range of use cases: String: Sequences of bytes, including text, serialized objects, and binary arrays used for caching, counters, and bitwise operations. JSON: Nested JSON documents that are indexed and searchable using JSONPath expressions and with Redis Search Array: Sparse, index-addressable collection of string values Hash: Field-value maps used to represent basic objects and store groupings of key-value pairs with support for hash field expiration (TTL) Redis Search: Use Redis as a document database, a vector database, a secondary index, and a search engine. Define indexes for hash and JSON documents and then use a rich query language for vector search, full-text search, geospatial queries, and aggregations. List: Linked lists of string values used as stacks, queues, and for queue management. Set: Unordered collection of unique strings used for tracking unique items, relations, and common set operations (intersections, unions, differences). Sorted set: Collection of unique strings ordered by an associated score used for leaderboards and rate limiters. Vector set (beta): Collection of vector embeddings used for semantic similarity search, semantic caching, semantic routing, and Retrieval Augmented Generation (RAG). Geospatial indexes: Coordinates used for finding nearby points within a given radius or bounding box. Bitmap: A set of bit-oriented operations defined on the string type used for efficient set representations and object permissions. Bitfield: Binary-encoded strings that let you set, increment, and get integer values of arbitrary bit length used for limited-range counters, numeric values, and multi-level object permissions such as role-based access control (RBAC) Hyperloglog: A probabilistic data structure for approximating the cardinality of a set used for analytics such as counting unique visits, form fills, etc. * Bloom filter: A probabilistic data structure to check if a given value is present in a set. Used for fraud detection, ad placement, and unique column (i.e. username/email/slug) checks. * Cuckoo filter: A probabilistic data structure for checking if a given value is present in a set while also allowing limited counting and deletions used in targeted advertising and coupon code validation. * t-digest: A probabilistic data structure used for estimating the percentile of a large dataset without having to store and order all the data points. Used for hardware/software monitoring, online gaming, network traffic monitoring, and predictive maintenance. * Top-k: A probabilistic data structure for finding the most frequent values in a data stream used for trend discovery. * Count-min sketch: A probabilistic data structure for estimating how many times a given value appears in a data stream used for sales volume calculations. Time series: Data points indexed in time order used for monitoring sensor data, asset tracking, and predictive analytics Pub/sub : A lightweight messaging capability. Publishers send messages to a channel, and subscribers receive messages from that channel. Stream : An append-only log with random access capabilities and complex consumption strategies such as consumer groups. Used for event sourcing, sensor monitoring, and notifications. Transaction: Allows the execution of a group of commands in a single step. A request sent by another client will never be served in the middle of the execution of a transaction. This guarantees that the commands are executed as a single isolated operation. Programmability: Upload and execute Lua scripts on the server. Scripts can employ programmatic control structures and use most of the commands while executing to access the database. Because scripts are executed on the server, reading and writing data from scripts is very efficient. Cloud hosted Redis Fully-managed Redis with real-time performance at scale. Redis Cloud Community Redis Community Resources Build Redis from source This section refers to building Redis from source. If you want to get up and running with Redis quickly without needing to build from source see the Getting started section . These instructions apply to Redis 8.10 and above. For versions lower than 8.10, see the 8.8 build instructions . Configuration files : the build steps below tell you to run ./src/redis-server redis.conf . Release tarballs bake the bundled modules' loadmodule lines and per-module settings directly into redis.conf during packaging, so an extracted release tarball is ready to run as-is. When building from a git checkout instead, that module config lives in the auto-generated redis-full.conf produced by make modules-update (and regenerated by make sync-redis-conf ) — run ./src/redis-server redis-full.conf there. Edit Redis-core settings in redis.conf . See modules/MODULES.md for the full config flow. Install dependencies and build Building Redis with all data structures (JSON, time series, Bloom / cuckoo / count-min / top-k, t-digest, and the Query Engine) needs a build toolchain plus a few version-sensitive dependencies — GCC/Clang, LLVM 21 , CMake 3.25–3.31.6 , Rust 1.94 , OpenSSL, Python 3, and assorted -dev libraries. Instead of a per-OS package list, the repo installs them for you with make bootstrap , which detects your OS and installs each bundled module's prerequisites. CMake version range matters. The modules require 3.25 ≤ CMake ≤ 3.31.6 — CMake 4.x is not supported and the build will fail with it. On distros that ship CMake 4.x by default (e.g. Ubuntu 26.04), pin a supported version, e.g. pip3 install 'cmake==3.31.6' . Note make bootstrap only installs CMake when it's missing or too old; it won't downgrade a pre-installed 4.x, so remove/pin that yourself. 1. Get the source Either works — the release tarball already bundles the module sources; a git checkout needs one extra step to fetch them: # A) Release tarball (recommended for building/running a release). # Replace <version>, e.g. 8.10.0 — extracts into redis-<version>/: wget -O redis- < version > .tar.gz https://github.com/redis/redis/releases/download/ < version > /redis-full.tar.gz tar xvf redis- < version > .tar.gz && cd redis- < version > # B) git checkout — clone the bundled modules once: git clone https://github.com/redis/redis.git && cd redis make modules-update 2. Install the build dependencies Pick whichever option fits your environment: Build inside the Docker build environment — recommended. The repo ships docker/Dockerfile.noble (Ubuntu 24.04) with every prerequisite baked in, so you build inside the container and never touch your host toolchain: docker build -f docker/Dockerfile.noble -t redis-build:noble . # Multi-arch (requires `docker buildx` configured): docker buildx build --platform linux/amd64,linux/arm64 \ -f docker/Dockerfile.noble -t redis-build:noble . # Build with the working tree mounted: docker run --rm -it -v " $PWD " :/workspace -w /workspace redis-build:noble \ bash -lc ' make -j"$(nproc)" && make run ' Install everything on a fresh machine or container. On a clean environment (for example a throwaway ubuntu:24.04 container), let bootstrap install every prerequisite for Redis core and all cloned modules: make bootstrap ⚠️ make bootstrap installs system packages and may override existing versions of shared tools (compiler, CMake, LLVM, …). Prefer option 1, or run it in a disposable container, if that matters on your machine. See only what's missing. To inspect which prerequisites are absent before installing anything, print one deduped list across Redis core and all modules: make bootstrap list Then install just the reported packages yourself. (Version-gated deps are shown as name (>= X) ; optional test/coverage deps are listed separately and don't fail the check.) Get the exact install commands to copy-paste. To run exactly what make bootstrap would, but only for the missing dependencies, use dry-run — it prints the precise install command for each missing dependency and installs nothing: make bootstrap dry-run The commands are printed per module , so a dependency shared by several modules appears once for each. Work through them iteratively: Copy-paste the commands for a module to install its dependencies. Re-run make bootstrap dry-run — the deps you just installed no longer show, so you now see only what's still missing for the remaining modules. Repeat until make bootstrap dry-run prints no install commands. Manual, per-OS install (no Docker, and you'd rather not let make bootstrap touch your host): follow the per-OS dependency instructions in the 8.8 README, which still lists them explicitly — https://github.com/redis/redis/tree/8.8#readme . 3. Build and run export BUILD_TLS=yes # optional — TLS support (needs OpenSSL dev libs) make -j " $( nproc ) " # Release tarball (module config is baked into redis.conf): ./src/redis-server redis.conf # From a git checkout, use the auto-generated module config instead: ./src/redis-server redis-full.conf make (same as make build / make all ) builds whatever is cloned under modules/*/src alongside Redis core. To build just the core data structures — even with modules cloned — use make build redis . Building Redis - flags and general notes Redis can be compiled and used on Linux, OSX, OpenBSD, NetBSD, FreeBSD. We support big endian and little endian architectures, and both 32 bit and 64-bit systems. It may compile on Solaris derived systems (for instance SmartOS) but our support for this platform is best effort and Redis is not guaranteed to work as well as on Linux, OSX, and *BSD. To build Redis with all the data structures (including JSON, time series, Bloom filter, cuckoo filter, count-min sketch, top-k, and t-digest) and with Redis Query Engine, make sure first that all the prerequisites are installed (see Install dependencies and build above), then clone the bundled modules once and build: make modules-update make make (same as make build / make all ) always builds whatever's cloned under modules/*/src alongside Redis core — there's no separate flag to opt in. If nothing is cloned yet, you get a core-only build. To build Redis with just the core data structures — even if modules are already cloned — use: make build redis To build with TLS support, you need OpenSSL development libraries (e.g. libssl-dev on Debian/Ubuntu) and the following flag in the make command: make BUILD_TLS=yes To build with systemd support, you need systemd development libraries (such as libsystemd-dev on Debian/Ubuntu or systemd-devel on CentOS), and the following flag: make USE_SYSTEMD=yes To append a suffix to Redis program names, add the following flag: make PROG_SUFFIX= " -alt " You can build a 32 bit Redis binary using: make 32bit After building Redis, it is a good idea to test it using: make test If TLS is built, running the tests with TLS enabled (you will need tcl-tls installed): ./utils/gen-test-certs.sh ./runtest --tls Redis supports compression of replication stream via zstd as of 8.10. To build with compression support you have to install zstd development libraries (e.g libzstd-dev on Debian/Ubuntu) and use the following flag when invoking the make command: make BUILD_COMPRESSION=yes Fixing build problems with dependencies or cached build options Redis has some dependencies which are included in the deps directory. make does not automatically rebuild dependencies even if something in the source code of dependencies changes. When you update the source code with git pull or when code inside the dependencies tree is modified in any other way, make sure to use the following command in order to really clean everything and rebuild from scratch: make distclean This will clean: jemalloc, lua, hiredis, linenoise and other dependencies. Also, if you force certain build options like 32bit target, no C compiler optimizations (for debugging purposes), and other similar build time options, those options are cached indefinitely until you issue a make distclean command. Fixing problems building 32 bit binaries If after building Redis with a 32 bit target you need to rebuild it with a 64 bit target, or the other way around, you need to perform a make distclean in the root directory of the Redis distribution. In case of build errors when trying to build a 32 bit binary of Redis, try the following steps: Install the package libc6-dev-i386 (also try g++-multilib). Try using the following command line instead of make 32bit : make CFLAGS="-m32 -march=native" LDFLAGS="-m32" Allocator Selecting a non-default memory allocator when building Redis is done by setting the MALLOC environment variable. Redis is compiled and linked against libc malloc by default, except for jemalloc being the default on Linux systems. This default was picked because jemalloc has proven to have fewer fragmentation problems than libc malloc. To force compiling against libc malloc, use: make MALLOC=libc To compile against jemalloc on Mac OS X systems, use: make MALLOC=jemalloc Monotonic clock By default, Redis will build using the POSIX clock_gettime function as the monotonic clock source. On most modern systems, the internal processor clock can be used to improve performance. Cautions can be found here: http://oliveryang.net/2015/09/pitfalls-of-TSC-usage/ On ARM aarch64 systems, the hardware clock is enabled by default because the ARM Generic Timer is architecturally guaranteed to be available and monotonic on all ARMv8-A processors (see the “The Generic Timer in AArch64 state” section of the Arm Architecture Reference Manual for Armv8-A ). To build with support for the processor's internal instruction clock on other architectures, use: make CFLAGS= " -DUSE_PROCESSOR_CLOCK " Verbose build Redis will build with a user-friendly colorized output by default. If you want to see a more verbose output, use the following: make V=1 Running Redis with TLS Please consult the TLS.md file for more information on how to use Redis with TLS. Running Redis with the Query Engine and optional proprietary Intel SVS-VAMANA optimisations License Disclaimer If you are using Redis Open Source under AGPLv3 or SSPLv1, you cannot use it together with the Intel Optimizations (Leanvec and LVQ binaries). The reason is that the Intel SVS license is not compatible with those licenses. The Leanvec and LVQ techniques are closed source and are only available for use with Redis Open Source when distributed under the RSALv2 license. For more details, please refer to the information provided by Intel here . By default, Redis with the Redis Query Engine supports SVS-VAMANA index with global 8-bit quantisation. To compile Redis with the Intel SVS-VAMANA optimisations, LeanVec and LVQ, use the following: make BUILD_INTEL_SVS_OPT=yes Alternatively, you can export the variable before running the build step for your platform: export BUILD_INTEL_SVS_OPT=yes make Code contributions By contributing code to the Redis project in any form, including sending a pull request via GitHub, a code fragment or patch via private email or public discussion groups, you agree to release your code under the terms of the Redis Software Grant and Contributor License Agreement. Please see the CONTRIBUTING.md file in this source distribution for more information. For security bugs and vulnerabilities, please see SECURITY.md and the description of the ability of users to backport security patches under Redis Open Source 7.4+ under BSDv3. Open Source Redis releases are subject to the following licenses: Version 7.2.x and prior releases are subject to BSDv3. These contributions to the original Redis core project are owned by their contributors and licensed under the 3BSDv3 license as referenced in the REDISCONTRIBUTIONS.txt file. Any copy of that license in this repository applies only to those contributions; Versions 7.4.x to 7.8.x are subject to your choice of RSALv2 or SSPLv1; and Version 8.0.x and subsequent releases are subject to the tri-license RSALv2/SSPLv1/AGPLv3 at your option as referenced in the LICENSE.txt file. Redis Trademarks The purpose of a trademark is to identify the goods and services of a person or company without causing confusion. As the registered owner of its name and logo, Redis accepts certain limited uses of its trademarks, but it has requirements that must be followed as described in its Trademark Guidelines available at: https://redis.io/legal/trademark-policy/ .

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ZeroSSL

SSL ProtectionFor AnyoneFast. Reliable. Free. Easily secure any site by putting SSL management on autopilot, supporting one-step validation and renewal via REST API. Free SSL certificates issued instantly online, supporting ACME clients, SSL monitoring, quick validation and automated SSL renewal via ZeroSSL Bot or REST API.

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ConvertKit

Connect with your fans, foster your community, and earn a living online with the only marketing platform built for creators, by creators.

FreemiumWindowsmacOSLinux

Kling 3 AI

Kling 3.0 is an AI video generation platform that turns text prompts or images into short, cinematic-style videos. It highlights motion control, multiple styles, HD/4K output options (plan-dependent), and includes commercial usage rights on paid plans.

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godot

godot is a free, open-source alternative to Unity . Godot Engine 2D and 3D cross-platform game engine Godot Engine is a feature-packed, cross-platform game engine to create 2D and 3D games from a unified interface. It provides a comprehensive set of common tools , so that users can focus on making games without having to reinvent the wheel. Games can be exported with one click to a number of platforms, including the major desktop platforms (Linux, macOS, Windows), mobile platforms (Android, iOS), as well as Web-based platforms and consoles . Free, open source and community-driven Godot is completely free and open source under the very permissive MIT license . No strings attached, no royalties, nothing. The users' games are theirs, down to the last line of engine code. Godot's development is fully independent and community-driven, empowering users to help shape their engine to match their expectations. It is supported by the Godot Foundation not-for-profit. Before being open sourced in February 2014 , Godot had been developed by Juan Linietsky and Ariel Manzur for several years as an in-house engine, used to publish several work-for-hire titles. Getting the engine Binary downloads Official binaries for the Godot editor and the export templates can be found on the Godot website . Compiling from source See the official docs for compilation instructions for every supported platform. Community and contributing Godot is not only an engine but an ever-growing community of users and engine developers. The main community channels are listed on the homepage . The best way to get in touch with the core engine developers is to join the Godot Contributors Chat . To get started contributing to the project, see the contributing guide . This document also includes guidelines for reporting bugs. Documentation and demos The official documentation is hosted on Read the Docs . It is maintained by the Godot community in its own GitHub repository . The class reference is also accessible from the Godot editor. We also maintain official demos in their own GitHub repository as well as a list of awesome Godot community resources . There are also a number of other learning resources provided by the community, such as text and video tutorials, demos, etc. Consult the community channels for more information.

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Mac Mouse Fix

Make Your $10 Mouse Better Than an Apple Trackpad!

FreemacOS

Origami Studio 3

Origami Studio is a free design tool created by Meta and available for Mac. It allows designers to rapidly build and share interactive interfaces. With a new canvas interface, dynamic layout, Figma & Sketch support and a ton of peformance improvements and new patches.

FreemacOS

Datadog

See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

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Countly

Countly is a first-party digital analytics and customer engagement platform offering on-premise or private cloud hosting for mobile, web, and desktop apps. Capture, analyze, and act on data across every device and touchpoint, to create meaningful connections with your users, all while prioritizing data ownership and control.

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Patches Answer

Patches Answer is a simple and fast solution hub for the Patches game on LinkedIn. Get daily answers, hints, and step-by-step solutions to solve every puzzle quickly and easily.

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openscreen

openscreen is a free, open-source alternative to Screen Studio . Note OpenScreen is now archived and no longer maintained. For continued maintenance and development, a community-driven spin-off led by one of the core contributors is available here: https://github.com/EtienneLescot/openscreen Warning This started as a side project that blew up; not production grade and you'll hit bugs, but hopefully it covers what you need. This project will soon be archived. OpenScreen OpenScreen is your free, open-source alternative to Screen Studio. If you don't want to pay $29/month for Screen Studio but want a version that does what most people seem to need - quick, polished product demos and walkthroughs you'd post on X, Reddit or Youtube. OpenScreen does not offer every Screen Studio feature, but covers a lot of the core functionality. Screen Studio is an awesome product and this is definitely not a 1:1 clone. If you just want something fully free and open source, this project should cover most of your needs. 100% free for both personal and commercial use. Use it, modify it, distribute it. Please respect the License. Note Software should be accessible. OpenScreen has no paid tiers, premium features, upsells, or functionality locked behind a paywall. Core Features Record a specific window, or your whole screen. Record microphone and system audio. Webcam overlay with picture-in-picture, drag-to-position, mirroring, and shape options. Auto or manual zooms with adjustable depth, duration, easing, and pixel-precise position; auto-zoom follows your cursor as you work. Custom cursor size, smoothing, and click effects, with cursor themes and post-recording path smoothing. Automatic captions for voiceovers, generated on-device with no upload (works offline). Wallpapers, solid colors, gradients, or your own background image. Motion blur. Crop, trim, and per-segment speed control on the timeline. Text, arrow, and image annotations, with text animation presets. Timeline snapping guides and an audio waveform to make trimming easier. Customizable keyboard shortcuts. Export to MP4 or GIF in multiple aspect ratios and resolutions. Languages supported: Arabic, English, Spanish, French, Italian, Japanese, Korean, Portuguese (Brazil), Russian, Turkish, Vietnamese, Simplified Chinese, and Traditional Chinese. Installation Download the latest installer for your platform from the GitHub Releases page. macOS The easiest way to install on macOS is via Homebrew : brew install --cask siddharthvaddem/openscreen/openscreen Brew automatically picks the right build for Apple Silicon or Intel, and verifies the download against a notarized signature so Gatekeeper won't block it. To update later: brew upgrade --cask openscreen To uninstall: brew uninstall --cask openscreen (add --zap to also remove app data) Manual install (if you prefer) If you'd rather grab the .dmg directly from the Releases page and encounter Gatekeeper blocking the app, you can bypass it by running the following command in your terminal after installation: xattr -rd com.apple.quarantine /Applications/Openscreen.app Note: Give your terminal Full Disk Access in System Settings > Privacy & Security to grant you access and then run the above command. After running this command, proceed to System Preferences > Security & Privacy to grant the necessary permissions for "screen recording" and "accessibility". Once permissions are granted, you can launch the app. Note Upgrading from an older version and hitting permission issues? If you already had OpenScreen installed and the new version won't record (Screen Recording or Accessibility keep failing even after you grant them), uninstall the old version, remove OpenScreen's existing entries under System Settings > Privacy & Security (both Screen Recording and Accessibility), then do a fresh install and grant the permissions again when prompted. Windows Install via winget : winget install SiddharthVaddem.OpenScreen To update later: winget upgrade SiddharthVaddem.OpenScreen To uninstall: winget uninstall SiddharthVaddem.OpenScreen If you'd rather grab the .exe installer directly, download it from the Releases page . Linux Three packages are published to the Releases page for each version. Pick the one that matches your distro: Debian / Ubuntu / Pop!_OS ( .deb ) sudo apt install ./Openscreen-Linux-latest.deb Arch / Manjaro ( .pacman ) sudo pacman -U Openscreen-Linux-latest.pacman Any distro ( .AppImage ) chmod +x Openscreen-Linux- * .AppImage ./Openscreen-Linux- * .AppImage NixOS / Nix (flake) Try without installing: nix run github:siddharthvaddem/openscreen Install into your user profile: nix profile install github:siddharthvaddem/openscreen For a NixOS system config (flake): { inputs . openscreen . url = "github:siddharthvaddem/openscreen" ; outputs = { nixpkgs , openscreen , ... } : { nixosConfigurations . < host > = nixpkgs . lib . nixosSystem { modules = [ openscreen . nixosModules . default { programs . openscreen . enable = true ; } ] ; } ; } ; } For Home Manager, use openscreen.homeManagerModules.default with the same programs.openscreen.enable = true; . You may need to grant screen recording permissions depending on your desktop environment. Sandbox error: If the AppImage fails to launch with a "sandbox" error, run it with --no-sandbox : ./Openscreen-Linux- * .AppImage --no-sandbox Platform differences Everything in the editor and export is the same on macOS, Windows, and Linux: zooms, backgrounds, motion blur, crop/trim/speed, blur regions, annotations, auto-captions, projects, export, and all languages. The differences are in capture , where macOS and Windows use a native pipeline that Linux doesn't have: Native recording : macOS (ScreenCaptureKit) and Windows (Windows Graphics Capture) record through a native pipeline for higher quality and clean window-level capture. Linux records through the browser pipeline instead. Custom cursors : on macOS and Windows the real cursor is captured (shape, type, and clicks), which powers the cursor themes, click effects, and editable cursor overlay. On Linux only the cursor position is captured (used for auto-zoom), so those cursor options aren't available. Webcam : captured natively on macOS and Windows; on Linux it's recorded through the browser, but still works as a picture-in-picture overlay. System audio support varies by OS: macOS : requires macOS 13+. On macOS 14.2+ you'll be prompted to grant audio capture permission. macOS 12 and below can't capture system audio (mic still works). Windows : works out of the box. Linux : needs PipeWire (default on Ubuntu 22.04+, Fedora 34+). Older PulseAudio-only setups may not capture system audio (mic should still work). License This project is licensed under the MIT License . By using this software, you agree that the authors are not liable for any issues, damages, or claims arising from its use.

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Supabase

Build production-grade applications with a Postgres database, Authentication, instant APIs, Realtime, Functions, Storage and Vector embeddings. Start for free.

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Lucidchart

Lucidchart is the intelligent diagramming application where seeing becomes doing. With this intuitive, cloud-based solution, everyone can work visually and collaborate in real time while building flowcharts, mockups, UML diagrams, and more. Sign up for free now.

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Redis Insight

Redis Insight is a visual tool that provides capabilities to design, develop, and optimize your Redis application. Query, analyse and interact with your Redis data. Redis Insight is an intuitive and efficient GUI for Redis, allowing you to interact with your databases and manage your data—with built-in support for Redis modules. Redis Insight Highlights: Browse, filter, visualise your key-value Redis data structures and see key values in different formats (including JSON, Hex, ASCII, etc.) CRUD support for lists, hashes, strings, sets, sorted sets, and streams CRUD support for JSON data structure Interactive tutorials to learn easily, among other things, how to leverage the native JSON data structure supporting structured querying and full-text search, including vector similarity search for your AI use cases Contextualised recommendations to optimize performance and memory usage. The list of recommendations gets updated as you interact with your database Profiler - analyze every command sent to Redis in real-time SlowLog - analyze slow operations in Redis instances based on the Slowlog command Pub/Sub - support for Redis pub/sub , enabling subscription to channels and posting messages to channels Bulk actions - Delete the keys in bulk based on the filters set in Browser or Tree view Workbench - advanced command line interface with intelligent command auto-complete, complex data visualizations and support for the raw mode Command auto-complete support for search and query capability, JSON and time series data structures Visualizations of your search and query indexes and results. Ability to build your own data visualization plugins Officially supported for Redis OSS, Redis Cloud . Works with Microsoft Azure Cache for Redis

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Aiproductphotography

AI Product Photography is a web-based generator that creates professional ecommerce assets from a single product upload. It helps online sellers on platforms like Amazon and Shopify build complete image sets without hiring a photographer for every new SKU. The tool solves the problem of inconsistent listing quality and high production costs. Users can generate studio white backgrounds, lifestyle scenes, and infographics while maintaining the visual accuracy of their physical products. One thing to keep in mind: the system works best when you start with a clear photo of the actual item.

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CodeWhale

CodeWhale is a free, open-source alternative to Claude Code . Codewhale Codewhale is an open source coding agent for your terminal, built in Rust and improved in public with the people who use it. 简体中文 · 日本語 · Tiếng Việt · Bahasa Indonesia · 한국어 · Español · Português · Русский · Українська · Français · Deutsch · 繁體中文 · हिन्दी · Türkçe · Italiano · Polski · العربية · Català Install npm install -g codewhale codewhale The first run helps you connect a provider or stay offline. Codewhale also supports Cargo, Docker, Nix, Scoop, prebuilt archives, Android/Termux, and a CNB mirror. See the installation guide . Use Talk to Codewhale the same way you would talk to a teammate: Fix the failing tests and explain what changed. Or run a task without opening the TUI: codewhale exec " fix the failing tests and explain what changed " Codewhale can read your repository, edit files, run commands, inspect results, and keep working toward a goal. You decide how much access it has. Why Codewhale Use the model you want. Connect hosted providers or local models through Ollama, vLLM, or SGLang. Switch provider and model with /model . Stay in control. Plan is read-only. Ask, Auto-Review, and Full Access make approval behavior visible. /undo reverts the last turn and /restore returns the workspace to an earlier snapshot. Keep long work organized. Save sessions, set a durable /goal , review workflows before they run, and coordinate agents without turning their internal instructions into your transcript. Extend the agent you already have. Connect MCP servers and skills, configure hooks, and keep agent roles as readable files in your project or personal settings. Run /help in the TUI for commands and keyboard shortcuts. Safety Codewhale runs on your machine with the access you grant it. Approval modes and repository rules limit what the agent may do; optional OS sandboxing adds a stronger execution boundary where supported. Unknown model prices stay unknown instead of being reported as free. Read authorization order for the exact policy stack and configuration for local settings. Documentation Providers and local models Agent teams MCP , hooks , and configuration Local web client All documentation Join the community Codewhale gets better when people use it, report what feels wrong, and help fix it. If a provider is missing, a workflow is awkward, or the terminal UI gets in your way, open an issue . If you know how to improve it, open a pull request . First contributions are welcome, and contributors keep credit for the work that lands. Join the Discord , or add Hunter on WeChat ( hunterbown ) and ask to join the Whale Brothers group. Project history Codewhale began as deepseek-tui and still preserves that configuration and session compatibility. It is now provider-neutral and independently maintained; it is not affiliated with any model provider. Thanks to every contributor and to the open source communities that helped the project grow. See the contributor record . License MIT

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Google Meet

Use Google Meet for secure online web conferencing calls and video chat as a part of Google Workspace.

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