openai-agents-go and go-agent
These two frameworks are competitors, as both aim to provide Go developers with a solution for building multi-agent systems, with **A** emphasizing lightweight design and **B** focusing on production readiness with graph-aware memory and UTCP-native tools.
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 go-agent
Protocol-Lattice/go-agent
An agent framework for Go with graph-aware memory, UTCP-native tools, and multi-agent orchestration. Built for production.
Provides RAG-powered memory with importance scoring and MMR retrieval across PostgreSQL/Qdrant/MongoDB backends, plus optimized performance through LRU caching and buffer pre-allocation. Exposes agents as UTCP tools for hierarchical coordination, with CodeMode generating tool calls from LLM outputs—enabling agent-to-agent communication without explicit orchestration code. Integrates pluggable adapters for Gemini, Anthropic, and Ollama with a declarative module system for composing specialist agents into workflows.
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