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.

AgentIn is a Python-based AI agent framework designed to accelerate the development of conversational and task-driven agents. It offers built-in memory modules to persist context, dynamic tool integration to call external APIs or local functions, and a flexible prompt templating system for customized interactions. Multi-agent orchestration enables parallel workflows, while logging and caching improve reliability and auditability. Easily configurable via YAML or Python code, AgentIn supports major LLM providers and can be extended with custom plugins for domain-specific capabilities.

Agent Protocol is a decentralized framework that allows users to build AI Agents capable of interacting with smart contracts, external APIs, and other agents. It offers a no-code Agent Studio for visual workflow design, a Marketplace to publish and monetize agents, and an SDK for programmatic integration. Agents can initiate token payments, perform cross-chain operations, and dynamically adapt to real-time data, making them ideal for DeFi, NFT automation, and oracle services.