Google Agent Development Kit (ADK)

A Python integration that runs Google Agent Development Kit (ADK) agents inside Temporal durable workflows. Its TemporalModel routes LLM calls through Temporal Activities, activity_tool wraps agent tools as retryable Activities, and GoogleAdkPlugin configures the worker to execute ADK workflows on a distributed Temporal system. Temporal records inputs and outputs, retries or replays failed steps, and replaces nondeterministic operations with workflow-safe equivalents; MCP tools can also run as Activities. Workflows can pause for human input through Temporal Signals and Updates, while the Temporal UI exposes LLM calls and tool executions for debugging. The integration supports local ADK development with direct-execution fallbacks outside a Temporal Workflow; the documentation identifies it as experimental with Temporal Python SDK 1.24.0.

KADATH (Kernel for Agentic Darwinian Adaptation, Tooling, and Heredity) is an evolutionary multi-agent runtime developed by i3t4an. It evolves populations of complete agents across reproducible epochs: an Architect turns a goal into a measurable benchmark, organisms attempt the goal, an independent Grader scores their evidence, and selection, mutation, reproduction, and replacement produce later generations. Each evolvable genome includes an agent's system prompt, Python implementation, tools, dependency declarations, and supporting files, rather than only a prompt or response. The kernel keeps the objective, benchmark, scoring, scheduler, lineage, database, deadlines, containers, and isolation rules outside the genome; agents can change only during the post-grade mutation phase. The interactive runtime asks for an OpenAI API key and model ID, then collects the goal, epoch duration, population size, and epoch count. Its local runtime prepares Docker-based PostgreSQL, MinIO, LiteLLM, and SearXNG services.

AgentOps is an open-source observability and developer-tools platform for building, evaluating, and monitoring AI agents. Its Python SDK records agent sessions and LLM calls for dashboard-based session replays, step-by-step execution graphs, debugging, analytics, cost tracking, and benchmarking. Developers instrument code with decorators for sessions, agents, operations, tasks, and workflows; these support nested span hierarchies, input and output recording, exception handling, asynchronous functions, generators, and custom attributes. The SDK provides integrations with agent frameworks and LLM systems including CrewAI, AG2/AutoGen, Agno, LangGraph, and the OpenAI Agents SDK, and the platform can be self-hosted with its dashboard and API backend. The app is released under the MIT license.

Data Agent Kit is an editor extension for working with data operations. It supports viewing data jobs, executing saved queries, monitoring data-flow and Spark jobs, running notebooks, and accessing data services.

Agent Deck is an open-source terminal dashboard for running and monitoring multiple AI coding agents in parallel. It displays each session’s status, active tool, working directory, and last prompt in real time, with Vim-style keyboard navigation for creating, focusing, closing, and renaming panes. It supports Claude Code and OpenCode through automatically installed hooks and runs as the single-binary `dot-agent-deck`, with native embedded terminal panes and no external terminal multiplexer required. The dashboard runs inside terminals including Ghostty, iTerm2, Alacritty, Kitty, and WezTerm, while preserving the agent clients’ existing shortcuts, skills, and configurations. Per-project TOML configuration can pair an agent with side panes for test runs, log tails, or `kubectl` watches. macOS and Linux installation is available through Homebrew, Nix, prebuilt binaries, or source builds; Windows use is currently through WSL. The project is distributed under the MIT license.