How do agents share context?

Pass context through the supervisor, or use a shared resource such as a database or file store that every agent can reach via MCP resources.

What happens if one agent fails?

Wrap cross-agent calls in a circuit breaker and give the supervisor a fallback: retry, skip the sub-task, or route to an alternative worker.

Can agents run in different languages?

Yes. MCP is language-agnostic, so a Python agent, a Node.js agent, and a Go agent can all participate in the same workflow.

advancedTechArticle

Multi-Agent Orchestration with MCP

Coordinate multiple specialized MCP servers behind a supervisor agent, with task delegation, parallel execution, and resilient error handling.

Quick Answer / TL;DR

Multi-agent MCP systems decompose a complex task into sub-tasks, route each to a specialized MCP-backed worker, run independent work in parallel, and let a supervisor synthesize the results. This avoids overloading a single agent's context window and isolates failures to one worker instead of the whole workflow.

Key Takeaways

A supervisor pattern routes sub-tasks to specialized workers by required tool, then synthesizes their results.
Wrap cross-agent calls in a circuit breaker so one failing worker cannot cascade into the whole workflow.
Start with two or three agents and clear single-responsibility boundaries before scaling further.

Supervisor pattern

A central agent decomposes the incoming task, assigns each sub-task to the worker whose MCP tools match what it needs, executes independent sub-tasks in parallel, and synthesizes a final result from the worker outputs.

typescript

class SupervisorAgent {
  private workers: Map<string, MCPClient> = new Map();

  async executeTask(task: string) {
    const subtasks = await this.decomposeTask(task);
    const results = await Promise.all(
      subtasks.map((subtask) => {
        const worker = this.selectWorker(subtask);
        return worker.callTool(subtask.tool, subtask.args);
      })
    );
    return this.synthesize(task, results);
  }

  private selectWorker(subtask: { requires: string[] }): MCPClient {
    if (subtask.requires.includes("database")) return this.workers.get("analysis-agent")!;
    if (subtask.requires.includes("web")) return this.workers.get("research-agent")!;
    throw new Error("No worker registered for this subtask");
  }
}

Resilience: circuit breakers and retries

A worker agent going down should not take the whole workflow with it. A circuit breaker stops calling a consistently-failing worker for a cooldown window, and exponential backoff spaces out retries for transient failures such as a rate limit or a brief network blip.

typescript

class CircuitBreaker {
  private failures = 0;
  private lastFailure = 0;
  constructor(private threshold = 5, private cooldownMs = 60000) {}

  async execute<T>(fn: () => Promise<T>): Promise<T> {
    if (this.failures >= this.threshold && Date.now() - this.lastFailure < this.cooldownMs) {
      throw new Error("Circuit breaker open");
    }
    try {
      const result = await fn();
      this.failures = 0;
      return result;
    } catch (error) {
      this.failures++;
      this.lastFailure = Date.now();
      throw error;
    }
  }
}