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C# Implementation (#2)

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C# implementation of SEP-1763

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
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Peder Holdgaard Pedersen 2026-01-28 00:53:44 +01:00 • committed by GitHub
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csharp/sdk/samples/InterceptorLlmSample/LlmObservabilityInterceptors.cs Normal file
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using ModelContextProtocol.Interceptors;
using ModelContextProtocol.Interceptors.Client;
using ModelContextProtocol.Interceptors.Protocol.Llm;
using System.Text.Json;
using System.Text.Json.Nodes;
/// <summary>
/// Observability interceptors for llm/completion events.
/// These interceptors log and monitor LLM requests/responses.
/// </summary>
[McpClientInterceptorType]
public partial class LlmObservabilityInterceptors
{
/// <summary>
/// Logs LLM request details for monitoring and debugging.
/// </summary>
[McpClientInterceptor(
Name = "request-logger",
Description = "Logs LLM request details",
Type = InterceptorType.Observability,
Events = [InterceptorEvents.LlmCompletion],
Phase = InterceptorPhase.Request)]
public static ObservabilityInterceptorResult LogRequest(JsonNode? payload)
{
if (payload is null)
{
return new ObservabilityInterceptorResult { Observed = false };
}
var request = payload.Deserialize<LlmCompletionRequest>();
if (request is null)
{
return new ObservabilityInterceptorResult { Observed = false };
}
// In a real implementation, this would send to a logging service
// Here we just capture the metrics
var messageCount = request.Messages.Count;
var estimatedTokens = request.Messages.Sum(m => (m.Content?.Length ?? 0) / 4);
var hasTools = request.Tools?.Count > 0;
return new ObservabilityInterceptorResult
{
Observed = true,
Info = new JsonObject
{
["event"] = "llm_request",
["model"] = request.Model,
["messageCount"] = messageCount,
["estimatedPromptTokens"] = estimatedTokens,
["maxTokens"] = request.MaxTokens,
["temperature"] = request.Temperature,
["hasTools"] = hasTools,
["toolCount"] = request.Tools?.Count ?? 0,
["timestamp"] = DateTimeOffset.UtcNow.ToString("O")
}
};
}
/// <summary>
/// Logs LLM response details including token usage.
/// </summary>
[McpClientInterceptor(
Name = "response-logger",
Description = "Logs LLM response details and usage metrics",
Type = InterceptorType.Observability,
Events = [InterceptorEvents.LlmCompletion],
Phase = InterceptorPhase.Response)]
public static ObservabilityInterceptorResult LogResponse(JsonNode? payload)
{
if (payload is null)
{
return new ObservabilityInterceptorResult { Observed = false };
}
var response = payload.Deserialize<LlmCompletionResponse>();
if (response is null)
{
return new ObservabilityInterceptorResult { Observed = false };
}
var hasToolCalls = response.Choices.Any(c => c.Message.ToolCalls?.Count > 0);
var finishReasons = response.Choices.Select(c => c.FinishReason?.ToString() ?? "unknown").ToArray();
return new ObservabilityInterceptorResult
{
Observed = true,
Info = new JsonObject
{
["event"] = "llm_response",
["id"] = response.Id,
["model"] = response.Model,
["choiceCount"] = response.Choices.Count,
["finishReasons"] = JsonNode.Parse($"[\"{string.Join("\", \"", finishReasons)}\"]"),
["hasToolCalls"] = hasToolCalls,
["promptTokens"] = response.Usage?.PromptTokens,
["completionTokens"] = response.Usage?.CompletionTokens,
["totalTokens"] = response.Usage?.TotalTokens,
["timestamp"] = DateTimeOffset.UtcNow.ToString("O")
}
};
}
/// <summary>
/// Tracks estimated costs based on token usage.
/// </summary>
[McpClientInterceptor(
Name = "cost-tracker",
Description = "Tracks estimated API costs based on token usage",
Type = InterceptorType.Observability,
Events = [InterceptorEvents.LlmCompletion],
Phase = InterceptorPhase.Response)]
public static ObservabilityInterceptorResult TrackCosts(JsonNode? payload)
{
if (payload is null)
{
return new ObservabilityInterceptorResult { Observed = false };
}
var response = payload.Deserialize<LlmCompletionResponse>();
if (response?.Usage is null)
{
return new ObservabilityInterceptorResult { Observed = false };
}
// Approximate GPT-4 pricing (example only, not accurate)
const decimal PromptCostPer1k = 0.03m;
const decimal CompletionCostPer1k = 0.06m;
var promptCost = (response.Usage.PromptTokens / 1000.0m) * PromptCostPer1k;
var completionCost = (response.Usage.CompletionTokens / 1000.0m) * CompletionCostPer1k;
var totalCost = promptCost + completionCost;
return new ObservabilityInterceptorResult
{
Observed = true,
Metrics = new Dictionary<string, double>
{
["promptTokens"] = response.Usage.PromptTokens,
["completionTokens"] = response.Usage.CompletionTokens,
["estimatedCostUsd"] = (double)totalCost
},
Info = new JsonObject
{
["event"] = "cost_tracking",
["model"] = response.Model,
["promptTokens"] = response.Usage.PromptTokens,
["completionTokens"] = response.Usage.CompletionTokens,
["estimatedPromptCostUsd"] = (double)promptCost,
["estimatedCompletionCostUsd"] = (double)completionCost,
["estimatedTotalCostUsd"] = (double)totalCost,
["currency"] = "USD",
["timestamp"] = DateTimeOffset.UtcNow.ToString("O")
}
};
}
}