Agent Router (MCP Client)
This agent demonstrates Agent Orchestration using the Model Context Protocol (MCP). It acts as a router that receives natural language queries and delegates the actual work to other specialized agents.
How it Works
- The Brain: Uses Anthropic’s Claude (via SDK) to understand user intent.
- The Tools: It connects to the
calculator-python agent via its auto-generated MCP endpoint.
- The Flow:
- User asks: “Calculate 25 * 4”
- Router Agent sees it has a
calculator tool.
- Router Agent calls
calculator-python via MCP (tools/call).
- Calculator returns
100.
- Router Agent responds: “The result is 100.”
Configuration
Requires an OPENAI_API_KEY or ANTHROPIC_API_KEY and the URL of the target agent.
env:
- ANTHROPIC_API_KEY=sk-...
- MCP_URL=https://your-ngrok-url/mcp/agents/calculator-python
For local development, you must use ngrok to expose the target agent’s MCP endpoint so the LLM provider can reach it.
Source Code
name: agent-router
runtime: nodejs20
module: agent.js
entrypoint: handler
# Memory configuration
memory: 256
timeout: 120
# Environment variables (hardcoded for now - secret management not yet implemented)
env:
- ANTHROPIC_API_KEY=sk-proj-**********************
- MCP_URL=https://0d768ec007d8.ngrok-free.app/mcp/agents/calculator-python
# Telemetry configuration
telemetry:
enabled: true
labels:
team: platform
tier: integration
use_case: agent_router
# Scaling configuration
scaling:
min_workers: 1
max_workers: 5
target_utilization: 1.5
scale_up_threshold: 2.0
scale_down_threshold: 0.3
scale_up_delay: "10s"
scale_down_delay: "30s"
queue_size: 20
/**
* Agent Router
*
* An Orpheus agent that uses Claude (via Anthropic SDK) to route requests
* to other Orpheus agents via MCP protocol. This demonstrates:
* 1. Agent-to-agent communication via MCP
* 2. Anthropic SDK MCP connector integration
* 3. Orchestration patterns with Orpheus
*/
import Anthropic from "@anthropic-ai/sdk";
// Environment variables (set in agent.yaml)
const ANTHROPIC_API_KEY = process.env.ANTHROPIC_API_KEY;
const MCP_URL = process.env.MCP_URL;
/**
* Orpheus handler for MCP client agent.
*
* @param {Object} inputData - Input with 'query' field
* @returns {Object} Response with result or error
*/
export async function handler(inputData) {
const query = inputData.query || inputData.input || "";
if (!query) {
return {
error: "No query provided",
usage: "Provide a 'query' field with your request",
agent: "agent-router",
};
}
if (!ANTHROPIC_API_KEY) {
return {
error: "ANTHROPIC_API_KEY not configured",
agent: "agent-router",
};
}
if (!MCP_URL) {
return {
error: "MCP_URL not configured",
agent: "agent-router",
};
}
try {
// Initialize Anthropic client with MCP beta header
const client = new Anthropic({
apiKey: ANTHROPIC_API_KEY,
defaultHeaders: {
"anthropic-beta": "mcp-client-2025-11-20",
},
});
// Call Claude with MCP connection to the target agent
const response = await client.messages.create({
model: "claude-sonnet-4-20250514",
max_tokens: 1024,
mcp_servers: [
{
type: "url",
url: MCP_URL,
name: "orpheus-target-agent",
},
],
tools: [
{
type: "mcp_toolset",
mcp_server_name: "orpheus-target-agent",
},
],
messages: [
{
role: "user",
content: query,
},
],
});
// Extract text response
let textResponse = "";
const toolCalls = [];
for (const block of response.content) {
if (block.type === "text") {
textResponse += block.text;
} else if (block.type === "tool_use" || block.type === "mcp_tool_use") {
toolCalls.push({
tool: block.name,
input: block.input,
server_name: block.server_name || null,
type: block.type,
});
}
}
return {
response: textResponse,
tool_calls: toolCalls,
stop_reason: response.stop_reason,
status: "success",
agent: "agent-router",
mcp_target: MCP_URL,
};
} catch (error) {
return {
error: error.message,
status: "error",
agent: "agent-router",
};
}
}
