Overview
Routing in MCP involves directing requests to the most suitable models or services based on content type, user context, and system load — ensuring efficient processing and optimal resource utilization.Content-based routing
Route to specialized models based on request type (code, creative, scientific)
Load balancing
Distribute requests across nodes using round-robin, response time, or content-aware strategies
Dynamic tool routing
Route tool calls to regional endpoints, specific API versions, or latency-optimized backends
Content-based routing
Content-based routing directs requests to specialized services based on what the request contains. Code generation goes to a code model; creative writing goes to a creative model.// .NET Example: Content-based routing
public class ContentBasedRouter
{
private readonly Dictionary<string, McpClient> _specializedClients;
private readonly RoutingClassifier _classifier;
public ContentBasedRouter()
{
_specializedClients = new Dictionary<string, McpClient>
{
["code"] = new McpClient("https://code-specialized-mcp.com"),
["creative"] = new McpClient("https://creative-specialized-mcp.com"),
["scientific"] = new McpClient("https://scientific-specialized-mcp.com"),
["general"] = new McpClient("https://general-mcp.com")
};
_classifier = new RoutingClassifier();
}
public async Task<McpResponse> RouteAndProcessAsync(
string prompt,
IDictionary<string, object> parameters = null)
{
string category = await _classifier.ClassifyPromptAsync(prompt);
var client = _specializedClients.ContainsKey(category)
? _specializedClients[category]
: _specializedClients["general"];
Console.WriteLine($"Routing to {category} specialized service");
return await client.SendPromptAsync(prompt, parameters);
}
private class RoutingClassifier
{
public Task<string> ClassifyPromptAsync(string prompt)
{
prompt = prompt.ToLowerInvariant();
if (prompt.Contains("code") || prompt.Contains("function") ||
prompt.Contains("program") || prompt.Contains("algorithm"))
return Task.FromResult("code");
if (prompt.Contains("story") || prompt.Contains("creative") ||
prompt.Contains("imagine") || prompt.Contains("design"))
return Task.FromResult("creative");
if (prompt.Contains("science") || prompt.Contains("research") ||
prompt.Contains("analyze") || prompt.Contains("study"))
return Task.FromResult("scientific");
return Task.FromResult("general");
}
}
}
Intelligent load balancing
Load balancing optimizes resource utilization and ensures high availability. Three strategies are shown below:| Strategy | Best for |
|---|---|
| Round-robin | Even distribution, equal-capacity nodes |
| Response time | Heterogeneous nodes, latency-sensitive workloads |
| Content-aware | Specialized nodes optimized for specific request types |
// Java: Intelligent load balancing with multiple strategies
public class McpLoadBalancer {
private final List<McpServerNode> serverNodes;
private final LoadBalancingStrategy strategy;
public McpLoadBalancer(List<McpServerNode> nodes, LoadBalancingStrategy strategy) {
this.serverNodes = new ArrayList<>(nodes);
this.strategy = strategy;
}
public McpResponse processRequest(McpRequest request) {
McpServerNode selectedNode = strategy.selectNode(serverNodes, request);
try {
return selectedNode.processRequest(request);
} catch (Exception e) {
selectedNode.recordFailure();
List<McpServerNode> remainingNodes = new ArrayList<>(serverNodes);
remainingNodes.remove(selectedNode);
if (!remainingNodes.isEmpty()) {
McpServerNode fallbackNode = strategy.selectNode(remainingNodes, request);
return fallbackNode.processRequest(request);
}
throw new RuntimeException("All MCP server nodes failed");
}
}
// Round-robin strategy
public static class RoundRobinStrategy implements LoadBalancingStrategy {
private AtomicInteger counter = new AtomicInteger(0);
@Override
public McpServerNode selectNode(List<McpServerNode> nodes, McpRequest request) {
List<McpServerNode> healthyNodes = nodes.stream()
.filter(McpServerNode::isHealthy)
.collect(Collectors.toList());
if (healthyNodes.isEmpty())
throw new RuntimeException("No healthy nodes available");
int index = counter.getAndIncrement() % healthyNodes.size();
return healthyNodes.get(index);
}
}
// Weighted response time strategy
public static class ResponseTimeStrategy implements LoadBalancingStrategy {
@Override
public McpServerNode selectNode(List<McpServerNode> nodes, McpRequest request) {
return nodes.stream()
.filter(McpServerNode::isHealthy)
.min(Comparator.comparing(McpServerNode::getAverageResponseTime))
.orElseThrow(() -> new RuntimeException("No healthy nodes"));
}
}
// Content-aware strategy
public static class ContentAwareStrategy implements LoadBalancingStrategy {
@Override
public McpServerNode selectNode(List<McpServerNode> nodes, McpRequest request) {
boolean isCodeRequest = request.getPrompt().contains("code") ||
request.getAllowedTools().contains("codeInterpreter");
Optional<McpServerNode> specializedNode = nodes.stream()
.filter(McpServerNode::isHealthy)
.filter(node -> isCodeRequest &&
node.getSpecialization().equals("code"))
.findFirst();
return specializedNode.orElse(
nodes.stream()
.filter(McpServerNode::isHealthy)
.min(Comparator.comparing(McpServerNode::getCurrentLoad))
.orElseThrow(() -> new RuntimeException("No healthy nodes"))
);
}
}
}
Dynamic tool routing
Tool routing directs tool calls to the most appropriate endpoint based on user context — such as regional endpoints for data residency or versioned endpoints for API compatibility.# Python: Dynamic tool routing
class McpToolRouter:
def __init__(self):
self.tool_endpoints = {
"weatherTool": "https://weather-service.example.com/api",
"calculatorTool": "https://calculator-service.example.com/compute",
"databaseTool": "https://database-service.example.com/query",
"searchTool": "https://search-service.example.com/search"
}
self.regional_endpoints = {
"us": {
"weatherTool": "https://us-west.weather-service.example.com/api",
"searchTool": "https://us.search-service.example.com/search"
},
"europe": {
"weatherTool": "https://eu.weather-service.example.com/api",
"searchTool": "https://eu.search-service.example.com/search"
}
}
self.tool_versions = {
"weatherTool": {
"default": "v2",
"v1": "https://weather-service.example.com/api/v1",
"v2": "https://weather-service.example.com/api/v2",
"beta": "https://weather-service.example.com/api/beta"
}
}
async def route_tool_request(self, tool_name, parameters, user_context=None):
endpoint = self._select_endpoint(tool_name, parameters, user_context)
if not endpoint:
raise ValueError(f"No endpoint available for tool: {tool_name}")
return await self._execute_tool_request(endpoint, tool_name, parameters)
def _select_endpoint(self, tool_name, parameters, user_context=None):
if tool_name not in self.tool_endpoints:
return None
base_endpoint = self.tool_endpoints[tool_name]
# Version routing
if tool_name in self.tool_versions:
version_info = self.tool_versions[tool_name]
requested_version = parameters.get("_version", version_info["default"])
if requested_version in version_info:
base_endpoint = version_info[requested_version]
# Regional routing
if user_context and "region" in user_context:
user_region = user_context["region"]
if user_region in self.regional_endpoints:
regional_tools = self.regional_endpoints[user_region]
if tool_name in regional_tools:
return regional_tools[tool_name]
return base_endpoint
async def _execute_tool_request(self, endpoint, tool_name, parameters):
async with aiohttp.ClientSession() as session:
async with session.post(
endpoint,
json={"toolName": tool_name, "parameters": parameters},
headers={"Content-Type": "application/json"}
) as response:
if response.status == 200:
return await response.json()
error_text = await response.text()
raise Exception(f"Tool execution failed: {error_text}")
Routing and sampling architecture
The diagram below shows how routing and sampling work together in a comprehensive MCP architecture:MCP Client
│
▼
Request Router ──► Content Analyzer ──► Sampling Configurator
│
▼
Load Balancer ──► Server Pool ──► Model Selector
│
┌───────────┼───────────┐
▼ ▼ ▼
Model A Model B Model C
│ │ │
└───────────┴───────────┘
│
Tool Router
│ │
Primary Tools Regional Tools
Combine content-aware routing with regional tool routing so that a French user’s weather query is routed to both the creative-writing model (if asking in a conversational tone) and the EU weather endpoint (for data residency compliance).