AgenticBook

Agent Protocol

agentprotocol.ai

Open API specification standardizing how AI agents expose their capabilities and accept tasks. Enables interoperability between agent frameworks, benchmarking tools, and deployment platforms. Growing adoption in CrewAI, AutoGPT, and other major frameworks.

StandardAPIInterop

More in Agent Community, Directories & Research

LangChain TemplatesDirectories & Marketplaces

Official collection of reference applications and production-ready LangChain templates. Covers RAG, extraction, chatbots, agents, and more — each deployable with a single command. The fastest way to bootstrap a production LangChain application.

LangChainTemplatesReference
DifyDirectories & Marketplaces

Open-source LLM application development platform that combines BaaS and LLMOps. Provides a visual workflow builder, RAG pipeline, agent framework, and model management in one product. One of the fastest-growing open-source AI application platforms.

Open SourcePlatformVisual
OpenAI GPT StoreAgent Aggregators & Visual Tools

OpenAI's official marketplace for custom ChatGPT agents (GPTs). Browse thousands of community-built specialized agents for coding, research, creative writing, and analysis — or publish your own GPT to reach millions of ChatGPT users without building a standalone product.

MarketplaceOpenAINo-Code
Superagent HubDirectories & Marketplaces

Community hub for sharing and discovering Superagent-based AI assistants and agent configurations. Browse pre-built agents for sales, support, and research use cases. Fork and deploy community agents directly to the Superagent cloud.

CommunityTemplatesHub
Hugging Face AgentsDirectories & Marketplaces

Transformers Agents is a multi-modal agent API built into the Hugging Face ecosystem. Provides a natural language interface for calling 100,000+ HF models as tools. Integrates with the Hub model, dataset, and Space ecosystem for end-to-end AI agent workflows.

PythonHuggingFaceMultimodal
AgentBenchResearch & Foundational Papers

Comprehensive benchmark for evaluating LLM-based agents across 8 distinct environments including code, databases, web browsing, and games. Reveals major performance gaps between open and closed models on real-world agentic tasks. The de-facto standard for comparing agent capabilities.

ResearchBenchmarkPaper