* [RuFlo v3.10.0](https://github.com/ruvnet/ruflo) – Enterprise-grade multi-agent orchestration platform for deploying, coordinating, and optimizing specialized AI agents.

* [Crush v0.75.0](https://github.com/charmbracelet/crush) – Terminal-based AI coding assistant supporting multiple LLMs, sessions, and extensible capabilities.

* [(S)AGE v8.0.0](https://github.com/l33tdawg/sage) – Persistent, consensus-validated institutional memory infrastructure for AI agents with confidence scoring and natural decay.

* [agent-relay v7.1.0](https://github.com/AgentWorkforce/relay) – Real-time messaging between AI agents.

* [Kandev v0.55.0](https://github.com/kdlbs/kandev) – Kanban-based development environment that orchestrates multiple AI agents, reviews changes, and manages parallel tasks.

* [Kelos v0.37.0](https://github.com/kelos-dev/kelos) – Kubernetes-native framework for orchestrating autonomous AI coding agents.

* [Nimbalyst v0.63.0](https://github.com/nimbalyst/nimbalyst) – Visual workspace for building and collaborating with coding agents across files, sessions, and tasks.

* [Git For database Systems v0.3.0](https://github.com/Guepard-Corp/gfs) – Git-like version control for databases enabling snapshots, branching, instant rollback, and AI agent integration.

* [agentsh v0.20.0](https://github.com/canyonroad/agentsh) – Secure policy-enforced execution gateway that intercepts file, network, process, and signal activity and emits structured audit events.

* [metro-mcp v0.12.0](https://github.com/steve228uk/metro-mcp) – Plugin-based MCP server connecting Metro to the Chrome DevTools Protocol for React Native runtime debugging, inspection, and automation without app code changes.

* [K-Dense BYOK v0.4.6](https://github.com/K-Dense-AI/k-dense-byok) – Desktop AI research assistant running locally with your API keys to orchestrate expert agents, file workflows, and web search.

* [agent-device v0.16.9](https://github.com/callstackincubator/agent-device) – CLI for controlling iOS and Android devices and emulators to enable AI agents to interact with apps and UIs.

* [Shep v1.208.0](https://github.com/shep-ai/shep) – Run multiple AI coding agents in parallel, each in its own isolated git worktree with automated commits, pushes, and PRs.

* [Nocturne: The Soul Anchor Protocol 2.5.4](https://github.com/Dataojitori/nocturne_memory) – URI-based, rollback-capable, visual MCP memory store providing persistent, structured memories across models, sessions, and tools.

* [MDA Open Spec v1.1.7](https://github.com/sno-ai/mda) – Markdown superset that compiles one source into multiple agent runtime document formats with typed relationships and Sigstore-backed integrity.

* [CAIPE 0.4.18](https://github.com/cnoe-io/ai-platform-engineering) – Community-driven multi-agent platform engineering system providing persona-driven agents, knowledge retrieval, and integrations for platform operations.

* [AgentOS v0.9.34](https://github.com/framerslab/agentos) – TypeScript framework for AI agents with persistent cognitive memory, runtime tool forging, and multi-agent orchestration.

* [AgentField v0.1.88](https://github.com/Agent-Field/agentfield) – Control-plane infrastructure that deploys, scales, and secures autonomous AI agents as observable, identity-aware backend services.

* [AgentOS v0.9.30](https://github.com/framersai/agentos) – TypeScript runtime for AI agents providing cognitive memory, adaptive behavior, and runtime tool synthesis.

* [Autopus-ADK v0.50.19](https://github.com/Insajin/autopus-adk) – Harness that orchestrates multiple AI coding agents into engineering workflows with planning, testing, code review, and security audits.

* [AI Maestro v0.35.31](https://github.com/23blocks-OS/ai-maestro) – Agent orchestrator providing persistent memory, agent-to-agent messaging, and a dashboard to manage agents across multiple machines.

* [ITOps Agent Platform v3.0.3](https://github.com/qinshihu/itops-agent-platform) – Enterprise-grade full-stack IT operations automation platform that composes AI agents into visual workflows for server management, alerts, diagnostics, log analysis, and scheduled tasks.

* [Qwery v0.2.3](https://github.com/Guepard-Corp/qwery-core) – Terminal-based AI data analyst converting natural-language queries into SQL, executing them locally, and returning answers.

* [Manifest manifest@6.6.1](https://github.com/mnfst/manifest) – Backend framework enabling data, storage, logic, and admin panel definition in a single YAML file.

* [Orloj v0.16.1](https://github.com/OrlojHQ/orloj) – Orchestration runtime for multi-agent AI systems, using YAML manifests to schedule, route, execute, and govern agents, tools, and policies.

* [atomic-agent v0.1.32](https://github.com/AtomicBot-ai/atomic-agent) – Local operator agent for llama.cpp that controls browser, files, shell, tasks, and approvals while keeping data and models local.

* [Voquill desktop-dev-v0.0.645](https://github.com/voquill/voquill) – Cross-platform AI voice-typing app that dictates into any desktop app, cleans transcripts with AI, and syncs a personal glossary.

* [Pane v1.1.146-nightly.202...](https://github.com/dcouple/Pane) – Terminal-first agent manager that runs any CLI AI agent, manages worktrees, and centralizes agent workflows.