| Definition |
A remote service or endpoint that allows AI agents to perform actions (e.g., search, code, schedule). |
A toolkit or library for building, managing, and orchestrating AI agents. |
| Primary Use |
Execute a specific task or function (e.g., web search, file access). |
Design and manage complex, multi-step, or multi-agent workflows. |
| Complexity |
Low — plug-and-play via HTTP calls or SDKs. |
Medium to high — requires programming logic and orchestration design. |
| Examples |
OpenAI Function Calling, Google Search API, Tavily, Weather API. |
LangChain, AutoGen, CrewAI, MetaGPT, LangGraph. |
| Scope |
Focused on single actions or tools. |
Coordinates multiple agents, tools, memory, and decision paths. |
| Agent Collaboration |
Not built-in — used individually by one agent. |
Supports multi-agent collaboration (e.g., planner ↔ executor). |
| Swarm Intelligence |
Not applicable. |
Some frameworks support decentralized or emergent agent behavior. |
| Observability & Control |
Limited — typically logs per request. |
Advanced — trace task flow, retries, states, and agent communication. |
| Best For |
Enhancing LLMs with external capabilities or tool use. |
Building agent ecosystems, automation workflows, or smart assistants. |
