Open Source Go Artificial Intelligence Software for Mac
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Go Artificial Intelligence Software for Mac
View 1754 business solutionsBrowse free open source Go Artificial Intelligence Software for Mac and projects below. Use the toggles on the left to filter open source Go Artificial Intelligence Software for Mac by OS, license, language, programming language, and project status.
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PicoClaw
Ultra-Efficient AI Assistant in Go
PicoClaw is an ultra-lightweight, open-source personal AI assistant written in Go, architected from the ground up to operate with extremely low memory usage (under 10 MB) and fast boot times, making it suitable for inexpensive hardware platforms and embedded devices. Inspired by earlier AI assistant projects like “nanobot,” it was refactored to emphasize resource efficiency while still supporting meaningful AI-driven interactions such as conversational workflows, planning tasks, and automation. PicoClaw can run on hardware costing as little as $10 and on resource-constrained environments like RISC-V or ARM boards, with cross-architecture portability achieved through a single self-contained binary. The project’s goals include broad platform support (including Linux, macOS, and multiple CPU architectures), rapid startup times that make the assistant feel responsive, and integration with popular messaging platforms via gateways or bots. -
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xiaohongshu-mcp
MCP for xiaohongshu.com
xiaohongshu-mcp is a Model Context Protocol (MCP) server that equips AI assistants with first-class tools for working on Xiaohongshu (Little Red Book), focusing on day-to-day creator and operator workflows rather than generic browsing. The project centers on authenticated actions and data access that matter to content operations, such as checking login state, publishing or scheduling content, fetching recommendations and search results, reading post details, and acting on comments. It’s packaged so MCP-capable clients (e.g., Claude Desktop, Cursor) can discover its tools via schemas instead of prompt guesswork, which improves reliability and reduces brittle automation. The repo highlights a growing community and provides links to a hosted landing page, signaling that the server is intended for practical use beyond a proof of concept. By exposing typed resources and procedures, it enables repeatable, auditable automation in social workflows where UI changes are frequent. -
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PhotoPrism
AI-Powered Photos App for the Decentralized Web 🌈💎✨
PhotoPrism® is an AI-Powered Photos App for the Decentralized Web. It makes use of the latest technologies to tag and find pictures automatically without getting in your way. You can run it at home, on a private server, or in the cloud. Our mission is to provide the most user- and privacy-friendly solution to keep your pictures organized and accessible. That's why PhotoPrism was built from the ground up to run wherever you need it, without compromising freedom, privacy, or functionality. -
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KrillinAI
Video translation and dubbing tool powered by LLMs
KrillinAI is an end-to-end content localization, translation, and dubbing tool aimed at helping creators transform videos into multiple languages with minimal manual effort. It integrates several stages of the pipeline: video acquisition (either from local files or remote via download tools), speech recognition (ASR), subtitle segmentation and alignment, machine translation (with context-aware translation to preserve semantics), and voice cloning + text-to-speech (TTS) to produce dubbed audio tracks. KrillinAI supports both landscape and portrait videos, which makes it suitable for a wide range of platforms — from YouTube to TikTok or other vertical-video sites — and ensures correct formatting and layout for the final video. The tool offers “one-click” workflows and desktop versions, lowering the barrier for users who may not be familiar with video editing or audio processing pipelines. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Telegram Drive
Telegram Drive
Telegram Drive is a powerful utility that enables you to organize your telegram files and much more. Teldrive stands out among similar tools, thanks to its implementation in Go, a language known for its efficiency. Its performance surpasses alternatives written in Python and other languages, with the exception of Rust. Teldrive not only excels in speed but also offers an intuitive user interface for efficient file interaction which other tool lacks. Its compatibility with Rclone further enhances file management. -
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Whishper
Transcribe any audio to text, translate and edit subtitles 100% locall
Open-source, local-first audio transcription and subtitling suite with a simple web UI. Thanks to open-source technologies, Whishper can run 100% offline. Your data never leaves your computer. Whishper allows you to translate your transcriptions to and from more than 60 languages thanks to Argos Translate and LibreTranslate. Download the transcriptions in many formats (json, txt, vtt, srt). Easily edit your subtitles right in the Web-UI. -
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VideoSrt
Windows-GUI
This is an open source Windows-GUI software tool that can recognize video speech and automatically generate subtitle SRT files. VideoSrtIt is written in Golanglanguage and developed based on lxn/walk Windows-GUI toolkit. Open source software tool that can recognize video speech and automatically generate subtitle SRT files. It is suitable for business scenarios that quickly and batch generate Chinese/English subtitles and text files for media (video/audio). Recognize video/audio speech to generate subtitle files (support Chinese-English translation, bilingual subtitles) Extract speech text from video/audio. Batch translation, filter processing/encoding SRT subtitle files. Using the Alibaba Cloud speech recognition interface, the accuracy is high, and the standard Mandarin/English recognition rate is over 95%. Video recognition does not need to upload the original video, which is convenient, fast and time-saving. -
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Milvus
Vector database for scalable similarity search and AI applications
Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. Average latency measured in milliseconds on trillion vector datasets. Rich APIs designed for data science workflows. Consistent user experience across laptop, local cluster, and cloud. Embed real-time search and analytics into virtually any application. Milvus’ built-in replication and failover/failback features ensure data and applications can maintain business continuity in the event of a disruption. Component-level scalability makes it possible to scale up and down on demand. -
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Gitleaks
Protect and discover secrets using Gitleaks
Gitleaks is a fast, lightweight, portable, and open-source secret scanner for git repositories, files, and directories. With over 6.8 million docker downloads, 11.2k GitHub stars, 1.7 million GitHub Downloads, thousands of weekly clones, and over 400k homebrew installs, gitleaks is the most trusted secret scanner among security professionals, enterprises, and developers. Gitleaks-Action is our official GitHub Action. You can use it to automatically run a gitleaks scan on all your team's pull requests and commits, or run on-demand scans. If you are scanning repos that belong to a GitHub organization account, then you'll have to obtain a license. Gitleaks can be installed using Homebrew, Docker, or Go. Gitleaks is also available in binary form for many popular platforms and OS types on the releases page. In addition, Gitleaks can be implemented as a pre-commit hook directly in your repo or as a GitHub action using Gitleaks-Action. -
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Anyquery
Query anything (GitHub, Notion, +40 more) with SQL and let LLMs
Anyquery is an open-source SQL query engine designed to allow users to query data from almost any source using a unified SQL interface. The system enables developers and analysts to run SQL queries on files, APIs, applications, and databases without needing separate connectors or query languages for each platform. Built on top of SQLite, the engine uses a plugin architecture that allows it to extend support to dozens of external services and data sources. Users can query structured files such as CSV, JSON, and Parquet as well as remote data sources like SaaS APIs, cloud storage services, and local applications. The platform also supports querying multiple data sources simultaneously and joining them together within a single SQL query, enabling powerful cross-system analysis. In addition to operating as a local query engine, the system can run as a MySQL-compatible server so that traditional database tools can connect to it. -
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Crush
The glamourous AI CLI coding agent for your favourite terminal 💘
Crush is a next-generation, terminal-based AI coding assistant developed by Charm, designed to seamlessly integrate with your tools, workflows, and preferred LLMs. It provides developers with an intuitive, session-based experience where multiple contexts can be managed across projects. With flexible model switching, Crush allows you to change providers mid-session while retaining conversation history. It enhances productivity by combining LSP (Language Server Protocol) support with extensible MCP (Model Context Protocol) integrations for richer coding context and external tool connectivity. Built for portability, it offers first-class support across macOS, Linux, Windows (PowerShell and WSL), and BSD systems. Backed by the Charm ecosystem, Crush is a stable, actively maintained evolution of the original OpenCode project. -
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Ninjabot
A fast cryptocurrency platform for trading bot in Go
A fast cryptocurrency trading bot framework implemented in Go. Ninjabot permits users to create and test custom strategies for spot markets. Ninjabot is an open-source platform that provides tools to implement custom strategies and backtests for trading cryptocurrencies in Go. Ninjabot CLI provides utilities commands to support backtesting and bot development. Currently, we only support Binance exchange. If you want to include support for other exchanges, you need to implement a new struct that implements the interface Exchange. You can check some examples in the exchange directory. You can create bots in telegram accessing BotFather. Telegram bot requires that your bot is running to control and get information about your account. -
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OpenCode
A powerful AI coding agent. Built for the terminal.
OpenCode is a terminal-based AI coding assistant designed to bring powerful AI models directly into your development workflow. Built in Go, it offers a smooth TUI (Terminal User Interface) experience powered by Bubble Tea, enabling seamless interaction without leaving the command line. It supports multiple AI providers, including OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Groq, Azure OpenAI, and GitHub Copilot. Developers can use it for intelligent code completion, debugging, file editing, and session management while staying entirely within their terminal environment. With support for the Language Server Protocol (LSP), OpenCode enhances code intelligence across multiple languages. Although archived, the project has evolved into Crush, actively maintained by the Charm team. -
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Casibase
Open-source enterprise-level AI knowledge base and MCP
Casibase is an open-source AI cloud platform designed to function as an enterprise knowledge base, container management system, and collaboration environment for AI-driven applications. The project combines knowledge management, messaging, and forum features with large language model integration to create an interactive platform for storing and querying domain-specific knowledge. Built with a separated frontend and backend architecture, Casibase provides a web-based administrative interface and supports high concurrency for enterprise environments. The platform integrates embedding techniques and prompt engineering to enable semantic knowledge retrieval and conversational interactions with stored data. It also supports integration with existing systems through database synchronization, allowing organizations to migrate data into the platform without major infrastructure changes. -
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GitHub Agentic Workflows
GitHub Agentic Workflows
GitHub Agentic Workflows is an experimental CLI extension and framework for the gh GitHub CLI that lets developers author automation driven by natural language specifications instead of hand-written code, compiling those descriptions into GitHub Actions workflows that run AI agents (like Copilot, Claude Code, or Codex) on schedule or in response to repository events. By writing intent in markdown files, a developer can quickly generate .yml Actions workflows that perform tasks such as summarizing issues, automating triage, generating reports, or maintaining documentation, all without manually crafting YAML logic from scratch. The system emphasizes safety and guardrails, running agents in sandboxed environments with minimal permissions by default, and using “safe outputs” to constrain what the workflow can write back into the repository. It includes tooling for compiling, testing, and iterating on agentic workflows locally and integrates with GitHub’s existing Actions ecosystem. -
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openclaw-kapso-whatsapp
Give your OpenClaw AI agent a WhatsApp number
openclaw-kapso-whatsapp is a plugin repository designed to extend the OpenClaw AI agent by giving it a dedicated WhatsApp phone number using the official Meta Cloud API via Kapso, enabling direct interaction through one of the most widely used messaging platforms. This integration allows the autonomous AI assistant to send and receive messages on WhatsApp, turning the agent into a real-world task performer accessible through text conversations. The plugin is built in Go and handles communication entirely through cloud APIs, avoiding the risk of bans that come with unofficial or reverse-engineered interfaces. Projects like this make it possible for OpenClaw users to automate tasks, interact with personal contacts, or provide AI-driven services without building a custom bot infrastructure from scratch. Because OpenClaw itself runs on the user’s own hardware and can access external services, this WhatsApp extension serves as a bridge between the AI agent and daily messaging workflows. -
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Crush
Glamourous agentic coding for all
Crush is an open-source, agentic code assistant that combines powerful AI capabilities with a flexible tool execution environment, enabling developers to extend and customize how AI interacts with codebases. Designed around the Agent Skills open standard, crush lets users install and manage reusable skill packages that teach the agent how to perform specific tasks, from browsing files to editing and transforming code. When first initialized in a project, it analyzes the codebase and generates contextual knowledge files that help the agent become more effective over time. By default, crush prompts for permission before executing tool calls for safety, but this behavior can be configured, and users can enable or disable specific tools to refine capabilities. It also supports custom provider configurations for different large language models and integrations, helping developers tailor the system to their workflow preferences. -
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CyberStrikeAI
CyberStrikeAI is an AI-native security testing platform built in Go
CyberStrikeAI is an AI-native security testing platform built in Go that brings autonomous penetration testing, vulnerability discovery, and attack chain analysis into a unified interface. The platform integrates over 100 security tools out of the box and pairs them with an intelligent orchestration engine that can be directed via natural language or policy definitions, allowing users to automate reconnaissance, scanning, exploitation, and reporting without manual sequencing of tools. It supports role-based testing, letting teams define security roles with tailored tool access and prompts, and includes a skills system that encapsulates specialized testing strategies that the AI can incorporate into its planning. Through comprehensive lifecycle management, results are tracked, aggregated, and visualized, with support for versioned persistence, search, and risk severity scoring. -
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Octelium
A next-gen FOSS self-hosted unified zero trust secure access platform
Octelium is an open source, self-hosted unified secure-access platform built for modern infrastructure and hybrid environments. It positions itself as more than a typical VPN; it supports zero-trust network access (ZTNA), “BeyondCorp”-style access, API/AI gateway functionality, and even serves as a PaaS-like deployment surface. One of its key strengths is identity-based, application-layer (L7) aware control, meaning access decisions are made per request, with context and policy rather than simple network-level allow/block rules. It supports both client-based (e.g., WireGuard/QUIC tunnels) and client-less access models, which makes it flexible for both human users and automated workloads. The project also highlights self-hosted, no hidden “server-side” locked components, giving organizations greater ownership and control over access, rather than relying on proprietary SaaS. -
20
Beelzebub
A secure low code honeypot framework
Beelzebub is an open-source cybersecurity framework designed to create intelligent honeypot environments for detecting and studying cyber attacks. Honeypots are systems intentionally exposed to attackers in order to capture malicious behavior, and Beelzebub enhances this concept by incorporating artificial intelligence and virtualization techniques. The platform allows organizations and researchers to deploy decoy services that mimic real infrastructure while recording attacker interactions. By using AI models to simulate realistic system behavior, the honeypot becomes harder for attackers to identify, increasing the likelihood that malicious activity can be observed and analyzed. The framework is designed with a low-code configuration approach so security teams can easily deploy honeypots for multiple services and ports. -
21
MCPTools
A command-line interface for interacting with MCP
mcptools is a command-line interface designed for interacting with Model Context Protocol (MCP) servers using both standard input/output and HTTP transport methods. It allows users to discover and call tools, list resources, and interact with MCP-compatible servers. The tool supports various output formats and includes features like an interactive shell, project scaffolding, and server alias management. -
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Beads
A memory upgrade for your coding agent
Beads is an open-source project providing a distributed, structured memory system for AI coding agents, replacing ad-hoc text plans with a git-backed graph that represents tasks, dependencies, and progress in a persistent, queryable format. Instead of storing plans as unstructured Markdown or ephemeral notes, Beads organizes agent state, task artifacts, and relationships as nodes and edges in a version-controlled graph so that long-horizon projects don’t lose context or coherence as the agent proceeds. This approach helps coding agents — and human collaborators — track which tasks depend on others, what has been done, and where workflows branch or reunify without losing important data. By leveraging Git as the storage backbone, the project ensures that memory is persistent, diffable, and sharable, with the ability to roll back, branch, or merge memory states just like source code. -
23
LocalAI
Self-hosted, community-driven, local OpenAI compatible API
Self-hosted, community-driven, local OpenAI compatible API. Drop-in replacement for OpenAI running LLMs on consumer-grade hardware. Free Open Source OpenAI alternative. No GPU is required. Runs ggml, GPTQ, onnx, TF compatible models: llama, gpt4all, rwkv, whisper, vicuna, koala, gpt4all-j, cerebras, falcon, dolly, starcoder, and many others. LocalAI is a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer-grade hardware, supporting multiple model families that are compatible with the ggml format. Does not require GPU. -
24
Pinchtab
High-performance browser automation bridge and orchestrator
Pinchtab is a lightweight browser automation backend built specifically for AI agents that need efficient, programmatic web control. Implemented as a small standalone HTTP server, it allows any agent or script to interact with web pages using simple API calls instead of heavyweight browser frameworks. The tool emphasizes accessibility-first snapshots that dramatically reduce token usage compared to screenshot-based approaches, making it cost-effective for large-scale automation. It launches and manages its own Chrome instance while remaining framework-agnostic, so it can be used with any language or agent system. Pinchtab also supports persistent sessions, stealth automation, and both headless and headed operation modes. The project’s goal is to provide fast, cheap, and portable browser control infrastructure for modern AI workflows. -
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Slack MCP Server
The most powerful MCP Slack Server with no permission requirements
Slack MCP Server is an open-source server implementation that connects Slack workspaces to AI systems through the Model Context Protocol (MCP). MCP is a standardized protocol that allows large language models and AI agents to securely interact with external tools and data sources such as messaging platforms, databases, or file systems. The slack-mcp-server acts as an intermediary layer that exposes Slack data and messaging functionality to AI clients while enforcing access rules and communication standards. Through this architecture, AI assistants can read message histories, interact with channels, and retrieve contextual information from Slack conversations in order to perform tasks such as automated analysis, collaboration assistance, or contextual code review. The server supports multiple communication transports, including standard input/output streams, HTTP, and Server-Sent Events, allowing flexible integration with different AI client environments.
