Multi-Agent Coordination provides a lightweight API to define AI agents, register them with a central coordinator, and dispatch tasks for collaborative problem solving. It handles message routing, concurrency control, and result aggregation. Developers can plug in custom agent behaviors, extend communication channels, and monitor interactions through built-in logging and hooks. This framework simplifies the development of distributed AI workflows, where each agent specializes in a subtask and the coordinator ensures smooth collaboration.

Wise Agents offers a comprehensive, searchable catalog of AI agent frameworks and platforms. It features filtering by category, programming language, license type, and more to help users zero in on the right tool. Each agent entry includes a detailed profile, key capabilities, GitHub and documentation links, and community ratings. The site is regularly updated through community contributions, ensuring the latest agent releases and developments are always available in one centralized resource.

A2A (Agent-to-Agent Architecture) is a Google open-source framework enabling the development and operation of distributed AI agents working together. It offers modular components to define agent roles, communication channels, and shared memory. Developers can integrate various LLM providers, customize agent behaviors, and orchestrate multi-step workflows. A2A includes built-in monitoring, error management, and replay capabilities to trace agent interactions. By providing a standardized protocol for agent discovery, message passing, and task allocation, A2A simplifies complex coordination patterns and enhances reliability when scaling agent-based applications across diverse environments.

The Agent Communication Protocol (ACP) is a formal framework designed to enable seamless interaction among autonomous AI agents. ACP specifies a set of message types, headers, and payload conventions, along with agent discovery and registry mechanisms. It supports conversation tracking, version negotiation, and standardized error reporting. By providing language-agnostic JSON schemas and transport-agnostic bindings, ACP reduces integration complexity and allows developers to compose scalable, interoperable multi-agent systems for use in customer service bots, robotic swarms, IoT orchestration, and collaborative AI workflows.

AI Agent Marketplace is built with Next.js and React to provide a centralized hub where users can browse, evaluate, and deploy a wide range of AI agents. The platform pulls agent metadata from community contributions, offering detailed descriptions, capability tags, and live in-browser demos. Users can filter agents by domain, function, or technology provider. For developers, the open-source repository includes a modular architecture with support for adding new agent entries, configuring API endpoints, and customizing UI components. Deployment options include hosting on Vercel or local Docker containers. By consolidating disparate AI agent projects into one searchable interface, the marketplace accelerates experimentation, collaboration, and integration into production workflows.

AI Agent Marketplace is a community-driven directory for AI agents, allowing developers, researchers, and enthusiasts to discover, evaluate, and contribute agents. Users can filter agents by category, view detailed functionality and integration instructions, and submit their own agents via pull requests. The platform aggregates metadata, links, and examples for each agent, making it easier to compare capabilities and find the right tool for specific use cases.

JADE is a Java-based agent development framework that simplifies the creation of distributed multi-agent systems. It provides FIPA-compliant infrastructure including a runtime environment, message transport, directory facilitator, and agent management. Developers write agent classes in Java, deploy them in containers, and use graphical tools like RMA and Sniffer for debugging and monitoring. JADE supports agent mobility, behavior scheduling, and lifecycle operations, enabling scalable and modular designs for research, IoT coordination, simulations, and enterprise automation.

Kaiban Agents Aggregator provides a unified dashboard to browse and manage AI agents built using the KaibanJS framework. Users can filter agents by category, view detailed documentation, test agent behavior, and deploy to staging or production with one click. The platform tracks runtime metrics and usage logs, enabling performance monitoring and quick iteration. Built-in collaboration tools allow multiple stakeholders to annotate, comment, and share configurations, while API integrations streamline embedding agents into existing applications or workflows.