Agent Orchestration

Agent orchestration is the layer that decides which agent or tool runs when, how results flow between steps, and what happens when a step fails. A single LLM call answers a question; an orchestrated workflow books the flight — it searches, compares, holds a seat, pays, and confirms, each step depending on the output of the last.

The orchestrator can be a framework (LangChain, CrewAI, AutoGen, n8n), a purpose-built planner agent that delegates to specialist sub-agents, or simply application code that sequences tool calls. What makes it orchestration rather than plain scripting is that the control flow is at least partly decided by a model at runtime — which tools to call, in what order, and whether the result is good enough to proceed.

Sequencing and dependencies: step three often needs the output of steps one and two. The orchestrator tracks intermediate state and feeds it forward, so a research agent's findings become the writing agent's source material.

Parallelism: independent steps — querying four data sources, scraping ten pages — should run concurrently. Good orchestrators fan work out and join the results, cutting wall-clock time dramatically.

Failure handling: tools time out, return garbage, or hit rate limits. Orchestration defines retries, fallbacks (try a different search server), and escalation to a human when the workflow genuinely cannot proceed.

Orchestration frameworks increasingly treat MCP servers as the standard tool abstraction. Instead of writing a bespoke integration for every API, the orchestrator connects to an MCP server, reads its tool list, and exposes those tools to whichever agent needs them. This is why the same Firecrawl or GitHub MCP server shows up in LangChain pipelines, n8n workflows, and Claude Desktop alike.

MCP also makes orchestration composable: a workflow can mix a filesystem server, a search server, and a database server from different authors, because they all speak the same protocol over stdio or Streamable HTTP.

Once a workflow spans premium tools, the orchestrator needs a way to pay mid-flow without a human pausing to enter a card. This is where x402 fits: when a paid MCP server responds with HTTP 402, the agent's wallet signs a per-call USDC payment, the call retries, and the workflow continues — settlement lands on Base in about two seconds, before the tool handler runs.

Practically, that means an orchestrated pipeline can budget per step: $0.01 for a search call here, $0.05 for an extraction there, all metered exactly to usage rather than to a stack of subscriptions the workflow may or may not exhaust.

The Loomal Index lists thousands of MCP servers across categories that orchestrated workflows typically chain together — search, web scraping, browser automation, databases, code execution. Browsing a category hub is a quick way to see what a multi-step agent pipeline can be assembled from, and which servers expose paid x402 endpoints an orchestrator can pay for autonomously.