openai-agents-go and agentcore
These two Go libraries are competitors, as both aim to provide frameworks or core functionalities for building AI agent applications, requiring a choice between them based on desired features and architectural approaches.
About openai-agents-go
nlpodyssey/openai-agents-go
A lightweight, powerful framework for multi-agent workflows in Go
Supports agent handoffs for control transfer, built-in tools (code interpreter, web search, file operations), and guardrails for safety validation—all compatible with OpenAI's Responses API, Chat Completions, and other LLM providers. Implements a turn-based agent loop that terminates when structured output or tool-free responses are produced, with Model Context Protocol integration for local and hosted tool servers. A direct Go port of OpenAI's Python Agents SDK maintaining API parity while offering fluent builder patterns for agent configuration, tools, and multi-agent orchestration.
About agentcore
voocel/agentcore
A minimal, composable Go library for building AI agent applications.
Implements a **double-loop architecture** (inner tool-steering loop + outer follow-up loop) with dependency injection, alongside built-in LLM adapters (OpenAI, Anthropic, Gemini via litellm), filesystem tools (read/write/edit/bash), and automatic context compaction via LLM summarization. Multi-agent orchestration works through a SubAgent tool supporting single/parallel/chain/background execution modes, while all lifecycle events (streaming, tool execution, errors) flow through a unified event channel for UI-agnostic subscription.
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