LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.

Beads - A memory upgrade for your coding agent

Automation engine to build, test and ship any codebase. Runs locally, in CI, or directly in the cloud

MCP Toolbox for Databases is an open source MCP server for databases.

Secure environments for developers and their agents

✨ Yao is a single-binary runtime to build and run autonomous agents — no Python, no Node.js, just define the role.

An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Entire is a new developer platform that hooks into your git workflow to capture AI agent sessions on every push, unifying your code with its context and reasoning.

⚡️ Open-source AI Gateway — Use any SDK to call 100+ LLMs. Built-in failover, load balancing, cost control & end-to-end tracing.

AI Agent Builder and Runtime by Docker Engineering

Cloud Native Agentic AI | Discord: https://bit.ly/kagentdiscord

AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.

Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations

♾️ Private Agent Fleet with Spec Coding. Each agent gets their own GPU-accelerated desktop. Run Claude, Codex, Gemini and open models on a full private AI Stack ♾️

kubectl for AI Agents

Convert Any OpenAPI V3 API to MCP Server

A developer experience centered on CUE. Unifies schemas, data models, deterministic and agentic code generation, workflow and task engine, dagger powered environments, coding assistant, and vscode extension; woven together on the CUE lattice. Squint harder if you can't see the cube :]

A powerful Go framework for building production-ready AI agents!

A developer CLI for working with Azure resources to build and deploy AI applications. Commands map to key workflow stages: code, build, deploy, and monitor.

🕵️‍♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.