```yaml
product: AlterLab
title: "Agent Orchestration — Web Scraping Glossary | AlterLab"
comparison_context: "AlterLab is an alternative to Firecrawl, ScrapingBee, and Bright Data."
source_url: https://alterlab.io/glossary/agent-orchestration
```

ai-agent

# Agent Orchestration

Agent orchestration coordinates multiple AI agents or tool calls in a structured workflow to complete complex, multi-step tasks that exceed a single LLM call.

A single LLM call can answer a simple question, but complex tasks — researching a topic across ten sources, extracting and comparing product data from multiple competitors, or filling out a web form based on retrieved information — require multiple steps and decisions. Agent orchestration frameworks (LangGraph, CrewAI, Anthropic's Agent SDK) chain LLM calls with tool use and branching logic to accomplish these tasks.

Orchestration patterns include: pipeline (sequential steps), router (a coordinator agent dispatches tasks to specialised sub-agents), and swarm (agents communicate peer-to-peer). Each pattern involves managing state (what has been done, what the results were), handling errors (retries, fallback agents), and synthesising outputs from multiple agents into a final result.

Web scraping is a foundational capability in agentic workflows. An orchestration framework that needs live data routes a sub-task to a scraping agent — using a tool like AlterLab's MCP server — and passes the structured result to the next agent in the pipeline.

### What is Agent Orchestration?

Agent orchestration coordinates multiple AI agents or tool calls in a structured workflow to complete complex, multi-step tasks that exceed a single LLM call.

### How does AlterLab handle Agent Orchestration?

Web scraping is a foundational capability in agentic workflows. An orchestration framework that needs live data routes a sub-task to a scraping agent — using a tool like AlterLab's MCP server — and passes the structured result to the next agent in the pipeline.

## Related Terms

[Tool UseTool use is the ability of an AI model to call external functions or APIs during generation, enabling it to retrieve live data, execute code, and interact with the world.](https://alterlab.io/glossary/tool-use)[MCP (Model Context Protocol)MCP is an open protocol by Anthropic that standardises how AI models connect to external tools, APIs, and data sources through a uniform server-client interface.](https://alterlab.io/glossary/mcp)[LLM (Large Language Model)A Large Language Model is a neural network trained on vast text corpora that can generate, summarise, translate, and reason over natural language at human level.](https://alterlab.io/glossary/llm)[RAG (Retrieval-Augmented Generation)RAG is an AI architecture that grounds LLM responses in retrieved documents, combining a vector search step with language model generation to reduce hallucinations.](https://alterlab.io/glossary/rag)[Scraping APIA managed web scraping service that abstracts proxy rotation, JavaScript rendering, and automatic website compatibility into a single HTTP endpoint.](https://alterlab.io/glossary/scraping-api)

## Extract Agent Orchestration data from any website

AlterLab returns clean, structured data from any public URL — no scraper infrastructure needed. Start free, no credit card required.

[View API docs](https://alterlab.io/docs/api/rest)

[Back to Glossary](https://alterlab.io/glossary)