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Najboljše prakse za razvoj MCP

Pregled

Ta lekcija se osredotoča na napredne najboljše prakse za razvoj, testiranje in uvajanje MCP strežnikov ter funkcij v proizvodnih okoljih. Ko MCP ekosistemi postajajo vse bolj kompleksni in pomembni, sledenje uveljavljenim vzorcem zagotavlja zanesljivost, vzdržljivost in interoperabilnost. Ta lekcija združuje praktične izkušnje, pridobljene iz resničnih MCP implementacij, da vas vodi pri ustvarjanju robustnih in učinkovitih strežnikov z učinkovitimi viri, navodili in orodji.

Cilji učenja

Do konca te lekcije boste sposobni:

  • Uporabiti industrijske najboljše prakse pri oblikovanju MCP strežnikov in funkcij
  • Ustvariti celovite strategije testiranja za MCP strežnike
  • Oblikovati učinkovite, večkrat uporabne vzorce delovnih tokov za kompleksne MCP aplikacije
  • Implementirati ustrezno ravnanje z napakami, beleženje in opazovanje v MCP strežnikih
  • Optimizirati MCP implementacije za zmogljivost, varnost in vzdržljivost

Dodatne reference

Za najnovejše informacije o najboljših praksah MCP glejte:

Najboljše prakse razvoja MCP orodij

Arhitekturna načela

1. Načelo enotne odgovornosti

Vsaka funkcija MCP naj ima jasen, osredotočen namen. Namesto ustvarjanja monolitnih orodij, ki poskušajo obravnavati več skrbi, razvijajte specializirana orodja, ki odlično opravljajo določene naloge.

Dober primer:

// A focused tool that does one thing well
public class WeatherForecastTool : ITool
{
    private readonly IWeatherService _weatherService;
    
    public WeatherForecastTool(IWeatherService weatherService)
    {
        _weatherService = weatherService;
    }
    
    public string Name => "weatherForecast";
    public string Description => "Gets weather forecast for a specific location";
    
    public ToolDefinition GetDefinition()
    {
        return new ToolDefinition
        {
            Name = Name,
            Description = Description,
            Parameters = new Dictionary<string, ParameterDefinition>
            {
                ["location"] = new ParameterDefinition
                {
                    Type = ParameterType.String,
                    Description = "City or location name"
                },
                ["days"] = new ParameterDefinition
                {
                    Type = ParameterType.Integer,
                    Description = "Number of forecast days",
                    Default = 3
                }
            },
            Required = new[] { "location" }
        };
    }
      public async Task<ToolResponse> ExecuteAsync(IDictionary<string, object> parameters)
    {
        var location = parameters["location"].ToString();
        var days = parameters.ContainsKey("days") 
            ? Convert.ToInt32(parameters["days"]) 
            : 3;
            
        var forecast = await _weatherService.GetForecastAsync(location, days);
        
        return new ToolResponse
        {
            Content = new List<ContentItem>
            {
                new TextContent(JsonSerializer.Serialize(forecast))
            }
        };
    }
}

Slab primer:

// A tool trying to do too many things
public class WeatherToolSuite : ITool
{
    public string Name => "weather";
    public string Description => "Weather-related functionality";
    
    public ToolDefinition GetDefinition()
    {
        return new ToolDefinition
        {
            Name = Name,
            Description = Description,
            Parameters = new Dictionary<string, ParameterDefinition>
            {
                ["action"] = new ParameterDefinition
                {
                    Type = ParameterType.String,
                    Description = "Weather action to perform",
                    Enum = new[] { "forecast", "history", "alerts", "radar" }
                },
                ["location"] = new ParameterDefinition
                {
                    Type = ParameterType.String,
                    Description = "City or location name"
                },
                // Many more properties for different actions...
            },
            required = new[] { "action", "location" }
        };
    }
    
    public async Task<ToolResponse> ExecuteAsync(ToolRequest request)
    {
        // Complex conditional logic to handle different actions
        var action = request.Parameters.GetProperty("action").GetString();
        var location = request.Parameters.GetProperty("location").GetString();
        
        switch (action)
        {
            case "forecast":
                // Forecast logic
                break;
            case "history":
                // Historical data logic
                break;
            // More cases...
            default:
                throw new ToolExecutionException($"Unknown action: {action}");
        }
        
        // Result processing
        // ...
    }
}

2. Injekcija odvisnosti in testabilnost

Oblikujte orodja, da prejmejo svoje odvisnosti skozi injekcijo konstruktorja, kar jih naredi testabilna in konfigurabilna:

// Java example with dependency injection
public class CurrencyConversionTool implements Tool {
    private final ExchangeRateService exchangeService;
    private final CacheService cacheService;
    private final Logger logger;
    
    // Dependencies injected through constructor
    public CurrencyConversionTool(
            ExchangeRateService exchangeService,
            CacheService cacheService,
            Logger logger) {
        this.exchangeService = exchangeService;
        this.cacheService = cacheService;
        this.logger = logger;
    }
    
    // Tool implementation
    // ...
}

3. Združljiva orodja

Oblikujte orodja, ki jih je mogoče združiti, da ustvarite bolj kompleksne delovne tokove:

# Python example showing composable tools
class DataFetchTool(Tool):
    def get_name(self):
        return "dataFetch"
    
    # Implementation...

class DataAnalysisTool(Tool):
    def get_name(self):
        return "dataAnalysis"
    
    # This tool can use results from the dataFetch tool
    async def execute_async(self, request):
        # Implementation...
        pass

class DataVisualizationTool(Tool):
    def get_name(self):
        return "dataVisualize"
    
    # This tool can use results from the dataAnalysis tool
    async def execute_async(self, request):
        # Implementation...
        pass

# These tools can be used independently or as part of a workflow

Najboljše prakse oblikovanja shem

Shema je pogodba med modelom in vašim orodjem. Dobro oblikovane sheme vodijo do boljše uporabnosti orodij.

1. Jasni opisi parametrov

Vedno vključite opisne informacije za vsak parameter:

public object GetSchema()
{
    return new {
        type = "object",
        properties = new {
            query = new { 
                type = "string", 
                description = "Search query text. Use precise keywords for better results." 
            },
            filters = new {
                type = "object",
                description = "Optional filters to narrow down search results",
                properties = new {
                    dateRange = new { 
                        type = "string", 
                        description = "Date range in format YYYY-MM-DD:YYYY-MM-DD" 
                    },
                    category = new { 
                        type = "string", 
                        description = "Category name to filter by" 
                    }
                }
            },
            limit = new { 
                type = "integer", 
                description = "Maximum number of results to return (1-50)",
                default = 10
            }
        },
        required = new[] { "query" }
    };
}

2. Omejitve validacije

Vključite omejitve validacije, da preprečite neveljavne vnose:

Map<String, Object> getSchema() {
    Map<String, Object> schema = new HashMap<>();
    schema.put("type", "object");
    
    Map<String, Object> properties = new HashMap<>();
    
    // Email property with format validation
    Map<String, Object> email = new HashMap<>();
    email.put("type", "string");
    email.put("format", "email");
    email.put("description", "User email address");
    
    // Age property with numeric constraints
    Map<String, Object> age = new HashMap<>();
    age.put("type", "integer");
    age.put("minimum", 13);
    age.put("maximum", 120);
    age.put("description", "User age in years");
    
    // Enumerated property
    Map<String, Object> subscription = new HashMap<>();
    subscription.put("type", "string");
    subscription.put("enum", Arrays.asList("free", "basic", "premium"));
    subscription.put("default", "free");
    subscription.put("description", "Subscription tier");
    
    properties.put("email", email);
    properties.put("age", age);
    properties.put("subscription", subscription);
    
    schema.put("properties", properties);
    schema.put("required", Arrays.asList("email"));
    
    return schema;
}

3. Dosledne strukture vračil

Ohranjajte doslednost v svojih strukturah odgovorov, da olajšate interpretacijo rezultatov modelom:

async def execute_async(self, request):
    try:
        # Process request
        results = await self._search_database(request.parameters["query"])
        
        # Always return a consistent structure
        return ToolResponse(
            result={
                "matches": [self._format_item(item) for item in results],
                "totalCount": len(results),
                "queryTime": calculation_time_ms,
                "status": "success"
            }
        )
    except Exception as e:
        return ToolResponse(
            result={
                "matches": [],
                "totalCount": 0,
                "queryTime": 0,
                "status": "error",
                "error": str(e)
            }
        )
    
def _format_item(self, item):
    """Ensures each item has a consistent structure"""
    return {
        "id": item.id,
        "title": item.title,
        "summary": item.summary[:100] + "..." if len(item.summary) > 100 else item.summary,
        "url": item.url,
        "relevance": item.score
    }

Ravnanje z napakami

Robustno ravnanje z napakami je ključno za MCP orodja, da ohranijo zanesljivost.

1. Prijazno ravnanje z napakami

Ravnajte z napakami na ustreznih ravneh in zagotovite informativna sporočila:

public async Task<ToolResponse> ExecuteAsync(ToolRequest request)
{
    try
    {
        string fileId = request.Parameters.GetProperty("fileId").GetString();
        
        try
        {
            var fileData = await _fileService.GetFileAsync(fileId);
            return new ToolResponse { 
                Result = JsonSerializer.SerializeToElement(fileData) 
            };
        }
        catch (FileNotFoundException)
        {
            throw new ToolExecutionException($"File not found: {fileId}");
        }
        catch (UnauthorizedAccessException)
        {
            throw new ToolExecutionException("You don't have permission to access this file");
        }
        catch (Exception ex) when (ex is IOException || ex is TimeoutException)
        {
            _logger.LogError(ex, "Error accessing file {FileId}", fileId);
            throw new ToolExecutionException("Error accessing file: The service is temporarily unavailable");
        }
    }
    catch (JsonException)
    {
        throw new ToolExecutionException("Invalid file ID format");
    }
    catch (Exception ex)
    {
        _logger.LogError(ex, "Unexpected error in FileAccessTool");
        throw new ToolExecutionException("An unexpected error occurred");
    }
}

2. Strukturirani odgovori na napake

Ko je mogoče, vrnite strukturirane informacije o napakah:

@Override
public ToolResponse execute(ToolRequest request) {
    try {
        // Implementation
    } catch (Exception ex) {
        Map<String, Object> errorResult = new HashMap<>();
        
        errorResult.put("success", false);
        
        if (ex instanceof ValidationException) {
            ValidationException validationEx = (ValidationException) ex;
            
            errorResult.put("errorType", "validation");
            errorResult.put("errorMessage", validationEx.getMessage());
            errorResult.put("validationErrors", validationEx.getErrors());
            
            return new ToolResponse.Builder()
                .setResult(errorResult)
                .build();
        }
        
        // Re-throw other exceptions as ToolExecutionException
        throw new ToolExecutionException("Tool execution failed: " + ex.getMessage(), ex);
    }
}

3. Logika ponovnega poskusa

Implementirajte ustrezno logiko ponovnega poskusa za prehodne napake:

async def execute_async(self, request):
    max_retries = 3
    retry_count = 0
    base_delay = 1  # seconds
    
    while retry_count < max_retries:
        try:
            # Call external API
            return await self._call_api(request.parameters)
        except TransientError as e:
            retry_count += 1
            if retry_count >= max_retries:
                raise ToolExecutionException(f"Operation failed after {max_retries} attempts: {str(e)}")
                
            # Exponential backoff
            delay = base_delay * (2 ** (retry_count - 1))
            logging.warning(f"Transient error, retrying in {delay}s: {str(e)}")
            await asyncio.sleep(delay)
        except Exception as e:
            # Non-transient error, don't retry
            raise ToolExecutionException(f"Operation failed: {str(e)}")

Optimizacija zmogljivosti

1. Predpomnjenje

Implementirajte predpomnjenje za drage operacije:

public class CachedDataTool : IMcpTool
{
    private readonly IDatabase _database;
    private readonly IMemoryCache _cache;
    
    public CachedDataTool(IDatabase database, IMemoryCache cache)
    {
        _database = database;
        _cache = cache;
    }
    
    public async Task<ToolResponse> ExecuteAsync(ToolRequest request)
    {
        var query = request.Parameters.GetProperty("query").GetString();
        
        // Create cache key based on parameters
        var cacheKey = $"data_query_{ComputeHash(query)}";
        
        // Try to get from cache first
        if (_cache.TryGetValue(cacheKey, out var cachedResult))
        {
            return new ToolResponse { Result = cachedResult };
        }
        
        // Cache miss - perform actual query
        var result = await _database.QueryAsync(query);
        
        // Store in cache with expiration
        var cacheOptions = new MemoryCacheEntryOptions()
            .SetAbsoluteExpiration(TimeSpan.FromMinutes(15));
            
        _cache.Set(cacheKey, JsonSerializer.SerializeToElement(result), cacheOptions);
        
        return new ToolResponse { Result = JsonSerializer.SerializeToElement(result) };
    }
    
    private string ComputeHash(string input)
    {
        // Implementation to generate stable hash for cache key
    }
}

2. Asinhrono obdelovanje

Uporabite asinhrone vzorce programiranja za operacije, ki so vezane na I/O:

public class AsyncDocumentProcessingTool implements Tool {
    private final DocumentService documentService;
    private final ExecutorService executorService;
    
    @Override
    public ToolResponse execute(ToolRequest request) {
        String documentId = request.getParameters().get("documentId").asText();
        
        // For long-running operations, return a processing ID immediately
        String processId = UUID.randomUUID().toString();
        
        // Start async processing
        CompletableFuture.runAsync(() -> {
            try {
                // Perform long-running operation
                documentService.processDocument(documentId);
                
                // Update status (would typically be stored in a database)
                processStatusRepository.updateStatus(processId, "completed");
            } catch (Exception ex) {
                processStatusRepository.updateStatus(processId, "failed", ex.getMessage());
            }
        }, executorService);
        
        // Return immediate response with process ID
        Map<String, Object> result = new HashMap<>();
        result.put("processId", processId);
        result.put("status", "processing");
        result.put("estimatedCompletionTime", ZonedDateTime.now().plusMinutes(5));
        
        return new ToolResponse.Builder().setResult(result).build();
    }
    
    // Companion status check tool
    public class ProcessStatusTool implements Tool {
        @Override
        public ToolResponse execute(ToolRequest request) {
            String processId = request.getParameters().get("processId").asText();
            ProcessStatus status = processStatusRepository.getStatus(processId);
            
            return new ToolResponse.Builder().setResult(status).build();
        }
    }
}

3. Dušenje virov

Implementirajte dušenje virov, da preprečite preobremenitev:

class ThrottledApiTool(Tool):
    def __init__(self):
        self.rate_limiter = TokenBucketRateLimiter(
            tokens_per_second=5,  # Allow 5 requests per second
            bucket_size=10        # Allow bursts up to 10 requests
        )
    
    async def execute_async(self, request):
        # Check if we can proceed or need to wait
        delay = self.rate_limiter.get_delay_time()
        
        if delay > 0:
            if delay > 2.0:  # If wait is too long
                raise ToolExecutionException(
                    f"Rate limit exceeded. Please try again in {delay:.1f} seconds."
                )
            else:
                # Wait for the appropriate delay time
                await asyncio.sleep(delay)
        
        # Consume a token and proceed with the request
        self.rate_limiter.consume()
        
        # Call API
        result = await self._call_api(request.parameters)
        return ToolResponse(result=result)

class TokenBucketRateLimiter:
    def __init__(self, tokens_per_second, bucket_size):
        self.tokens_per_second = tokens_per_second
        self.bucket_size = bucket_size
        self.tokens = bucket_size
        self.last_refill = time.time()
        self.lock = asyncio.Lock()
    
    async def get_delay_time(self):
        async with self.lock:
            self._refill()
            if self.tokens >= 1:
                return 0
            
            # Calculate time until next token available
            return (1 - self.tokens) / self.tokens_per_second
    
    async def consume(self):
        async with self.lock:
            self._refill()
            self.tokens -= 1
    
    def _refill(self):
        now = time.time()
        elapsed = now - self.last_refill
        
        # Add new tokens based on elapsed time
        new_tokens = elapsed * self.tokens_per_second
        self.tokens = min(self.bucket_size, self.tokens + new_tokens)
        self.last_refill = now

Najboljše prakse varnosti

1. Validacija vnosa

Vedno temeljito preverite vhodne parametre:

public async Task<ToolResponse> ExecuteAsync(ToolRequest request)
{
    // Validate parameters exist
    if (!request.Parameters.TryGetProperty("query", out var queryProp))
    {
        throw new ToolExecutionException("Missing required parameter: query");
    }
    
    // Validate correct type
    if (queryProp.ValueKind != JsonValueKind.String)
    {
        throw new ToolExecutionException("Query parameter must be a string");
    }
    
    var query = queryProp.GetString();
    
    // Validate string content
    if (string.IsNullOrWhiteSpace(query))
    {
        throw new ToolExecutionException("Query parameter cannot be empty");
    }
    
    if (query.Length > 500)
    {
        throw new ToolExecutionException("Query parameter exceeds maximum length of 500 characters");
    }
    
    // Check for SQL injection attacks if applicable
    if (ContainsSqlInjection(query))
    {
        throw new ToolExecutionException("Invalid query: contains potentially unsafe SQL");
    }
    
    // Proceed with execution
    // ...
}

2. Preverjanje dovoljenj

Implementirajte ustrezne preverbe dovoljenj:

@Override
public ToolResponse execute(ToolRequest request) {
    // Get user context from request
    UserContext user = request.getContext().getUserContext();
    
    // Check if user has required permissions
    if (!authorizationService.hasPermission(user, "documents:read")) {
        throw new ToolExecutionException("User does not have permission to access documents");
    }
    
    // For specific resources, check access to that resource
    String documentId = request.getParameters().get("documentId").asText();
    if (!documentService.canUserAccess(user.getId(), documentId)) {
        throw new ToolExecutionException("Access denied to the requested document");
    }
    
    // Proceed with tool execution
    // ...
}

3. Ravnanje z občutljivimi podatki

Ravnajte previdno z občutljivimi podatki:

class SecureDataTool(Tool):
    def get_schema(self):
        return {
            "type": "object",
            "properties": {
                "userId": {"type": "string"},
                "includeSensitiveData": {"type": "boolean", "default": False}
            },
            "required": ["userId"]
        }
    
    async def execute_async(self, request):
        user_id = request.parameters["userId"]
        include_sensitive = request.parameters.get("includeSensitiveData", False)
        
        # Get user data
        user_data = await self.user_service.get_user_data(user_id)
        
        # Filter sensitive fields unless explicitly requested AND authorized
        if not include_sensitive or not self._is_authorized_for_sensitive_data(request):
            user_data = self._redact_sensitive_fields(user_data)
        
        return ToolResponse(result=user_data)
    
    def _is_authorized_for_sensitive_data(self, request):
        # Check authorization level in request context
        auth_level = request.context.get("authorizationLevel")
        return auth_level == "admin"
    
    def _redact_sensitive_fields(self, user_data):
        # Create a copy to avoid modifying the original
        redacted = user_data.copy()
        
        # Redact specific sensitive fields
        sensitive_fields = ["ssn", "creditCardNumber", "password"]
        for field in sensitive_fields:
            if field in redacted:
                redacted[field] = "REDACTED"
        
        # Redact nested sensitive data
        if "financialInfo" in redacted:
            redacted["financialInfo"] = {"available": True, "accessRestricted": True}
        
        return redacted

Najboljše prakse testiranja za MCP orodja

Celovito testiranje zagotavlja, da MCP orodja delujejo pravilno, obravnavajo robne primere in se pravilno integrirajo s preostalim sistemom.

Enotno testiranje

1. Testirajte vsako orodje ločeno

Ustvarite osredotočene teste za funkcionalnost vsakega orodja:

[Fact]
public async Task WeatherTool_ValidLocation_ReturnsCorrectForecast()
{
    // Arrange
    var mockWeatherService = new Mock<IWeatherService>();
    mockWeatherService
        .Setup(s => s.GetForecastAsync("Seattle", 3))
        .ReturnsAsync(new WeatherForecast(/* test data */));
    
    var tool = new WeatherForecastTool(mockWeatherService.Object);
    
    var request = new ToolRequest(
        toolName: "weatherForecast",
        parameters: JsonSerializer.SerializeToElement(new { 
            location = "Seattle", 
            days = 3 
        })
    );
    
    // Act
    var response = await tool.ExecuteAsync(request);
    
    // Assert
    Assert.NotNull(response);
    var result = JsonSerializer.Deserialize<WeatherForecast>(response.Result);
    Assert.Equal("Seattle", result.Location);
    Assert.Equal(3, result.DailyForecasts.Count);
}

[Fact]
public async Task WeatherTool_InvalidLocation_ThrowsToolExecutionException()
{
    // Arrange
    var mockWeatherService = new Mock<IWeatherService>();
    mockWeatherService
        .Setup(s => s.GetForecastAsync("InvalidLocation", It.IsAny<int>()))
        .ThrowsAsync(new LocationNotFoundException("Location not found"));
    
    var tool = new WeatherForecastTool(mockWeatherService.Object);
    
    var request = new ToolRequest(
        toolName: "weatherForecast",
        parameters: JsonSerializer.SerializeToElement(new { 
            location = "InvalidLocation", 
            days = 3 
        })
    );
    
    // Act & Assert
    var exception = await Assert.ThrowsAsync<ToolExecutionException>(
        () => tool.ExecuteAsync(request)
    );
    
    Assert.Contains("Location not found", exception.Message);
}

2. Testiranje validacije shem

Preverite, da so sheme veljavne in pravilno uveljavljajo omejitve:

@Test
public void testSchemaValidation() {
    // Create tool instance
    SearchTool searchTool = new SearchTool();
    
    // Get schema
    Object schema = searchTool.getSchema();
    
    // Convert schema to JSON for validation
    String schemaJson = objectMapper.writeValueAsString(schema);
    
    // Validate schema is valid JSONSchema
    JsonSchemaFactory factory = JsonSchemaFactory.byDefault();
    JsonSchema jsonSchema = factory.getJsonSchema(schemaJson);
    
    // Test valid parameters
    JsonNode validParams = objectMapper.createObjectNode()
        .put("query", "test query")
        .put("limit", 5);
        
    ProcessingReport validReport = jsonSchema.validate(validParams);
    assertTrue(validReport.isSuccess());
    
    // Test missing required parameter
    JsonNode missingRequired = objectMapper.createObjectNode()
        .put("limit", 5);
        
    ProcessingReport missingReport = jsonSchema.validate(missingRequired);
    assertFalse(missingReport.isSuccess());
    
    // Test invalid parameter type
    JsonNode invalidType = objectMapper.createObjectNode()
        .put("query", "test")
        .put("limit", "not-a-number");
        
    ProcessingReport invalidReport = jsonSchema.validate(invalidType);
    assertFalse(invalidReport.isSuccess());
}

3. Testi ravnanja z napakami

Ustvarite posebne teste za pogoje napak:

@pytest.mark.asyncio
async def test_api_tool_handles_timeout():
    # Arrange
    tool = ApiTool(timeout=0.1)  # Very short timeout
    
    # Mock a request that will time out
    with aioresponses() as mocked:
        mocked.get(
            "https://api.example.com/data",
            callback=lambda *args, **kwargs: asyncio.sleep(0.5)  # Longer than timeout
        )
        
        request = ToolRequest(
            tool_name="apiTool",
            parameters={"url": "https://api.example.com/data"}
        )
        
        # Act & Assert
        with pytest.raises(ToolExecutionException) as exc_info:
            await tool.execute_async(request)
        
        # Verify exception message
        assert "timed out" in str(exc_info.value).lower()

@pytest.mark.asyncio
async def test_api_tool_handles_rate_limiting():
    # Arrange
    tool = ApiTool()
    
    # Mock a rate-limited response
    with aioresponses() as mocked:
        mocked.get(
            "https://api.example.com/data",
            status=429,
            headers={"Retry-After": "2"},
            body=json.dumps({"error": "Rate limit exceeded"})
        )
        
        request = ToolRequest(
            tool_name="apiTool",
            parameters={"url": "https://api.example.com/data"}
        )
        
        # Act & Assert
        with pytest.raises(ToolExecutionException) as exc_info:
            await tool.execute_async(request)
        
        # Verify exception contains rate limit information
        error_msg = str(exc_info.value).lower()
        assert "rate limit" in error_msg
        assert "try again" in error_msg

Integracijsko testiranje

1. Testiranje verige orodij

Preverite delovanje orodij skupaj v pričakovanih kombinacijah:

[Fact]
public async Task DataProcessingWorkflow_CompletesSuccessfully()
{
    // Arrange
    var dataFetchTool = new DataFetchTool(mockDataService.Object);
    var analysisTools = new DataAnalysisTool(mockAnalysisService.Object);
    var visualizationTool = new DataVisualizationTool(mockVisualizationService.Object);
    
    var toolRegistry = new ToolRegistry();
    toolRegistry.RegisterTool(dataFetchTool);
    toolRegistry.RegisterTool(analysisTools);
    toolRegistry.RegisterTool(visualizationTool);
    
    var workflowExecutor = new WorkflowExecutor(toolRegistry);
    
    // Act
    var result = await workflowExecutor.ExecuteWorkflowAsync(new[] {
        new ToolCall("dataFetch", new { source = "sales2023" }),
        new ToolCall("dataAnalysis", ctx => new { 
            data = ctx.GetResult("dataFetch"),
            analysis = "trend" 
        }),
        new ToolCall("dataVisualize", ctx => new {
            analysisResult = ctx.GetResult("dataAnalysis"),
            type = "line-chart"
        })
    });
    
    // Assert
    Assert.NotNull(result);
    Assert.True(result.Success);
    Assert.NotNull(result.GetResult("dataVisualize"));
    Assert.Contains("chartUrl", result.GetResult("dataVisualize").ToString());
}

2. Testiranje MCP strežnikov

Testirajte MCP strežnik s popolno registracijo orodij in izvedbo:

@SpringBootTest
@AutoConfigureMockMvc
public class McpServerIntegrationTest {
    
    @Autowired
    private MockMvc mockMvc;
    
    @Autowired
    private ObjectMapper objectMapper;
    
    @Test
    public void testToolDiscovery() throws Exception {
        // Test the discovery endpoint
        mockMvc.perform(get("/mcp/tools"))
            .andExpect(status().isOk())
            .andExpect(jsonPath("$.tools").isArray())
            .andExpect(jsonPath("$.tools[*].name").value(hasItems(
                "weatherForecast", "calculator", "documentSearch"
            )));
    }
    
    @Test
    public void testToolExecution() throws Exception {
        // Create tool request
        Map<String, Object> request = new HashMap<>();
        request.put("toolName", "calculator");
        
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("operation", "add");
        parameters.put("a", 5);
        parameters.put("b", 7);
        request.put("parameters", parameters);
        
        // Send request and verify response
        mockMvc.perform(post("/mcp/execute")
            .contentType(MediaType.APPLICATION_JSON)
            .content(objectMapper.writeValueAsString(request)))
            .andExpect(status().isOk())
            .andExpect(jsonPath("$.result.value").value(12));
    }
    
    @Test
    public void testToolValidation() throws Exception {
        // Create invalid tool request
        Map<String, Object> request = new HashMap<>();
        request.put("toolName", "calculator");
        
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("operation", "divide");
        parameters.put("a", 10);
        // Missing parameter "b"
        request.put("parameters", parameters);
        
        // Send request and verify error response
        mockMvc.perform(post("/mcp/execute")
            .contentType(MediaType.APPLICATION_JSON)
            .content(objectMapper.writeValueAsString(request)))
            .andExpect(status().isBadRequest())
            .andExpect(jsonPath("$.error").exists());
    }
}

3. Testiranje od konca do konca

Preverite celotne delovne tokove od modela do izvedbe orodja:

@pytest.mark.asyncio
async def test_model_interaction_with_tool():
    # Arrange - Set up MCP client and mock model
    mcp_client = McpClient(server_url="http://localhost:5000")
    
    # Mock model responses
    mock_model = MockLanguageModel([
        MockResponse(
            "What's the weather in Seattle?",
            tool_calls=[{
                "tool_name": "weatherForecast",
                "parameters": {"location": "Seattle", "days": 3}
            }]
        ),
        MockResponse(
            "Here's the weather forecast for Seattle:\n- Today: 65°F, Partly Cloudy\n- Tomorrow: 68°F, Sunny\n- Day after: 62°F, Rain",
            tool_calls=[]
        )
    ])
    
    # Mock weather tool response
    with aioresponses() as mocked:
        mocked.post(
            "http://localhost:5000/mcp/execute",
            payload={
                "result": {
                    "location": "Seattle",
                    "forecast": [
                        {"date": "2023-06-01", "temperature": 65, "conditions": "Partly Cloudy"},
                        {"date": "2023-06-02", "temperature": 68, "conditions": "Sunny"},
                        {"date": "2023-06-03", "temperature": 62, "conditions": "Rain"}
                    ]
                }
            }
        )
        
        # Act
        response = await mcp_client.send_prompt(
            "What's the weather in Seattle?",
            model=mock_model,
            allowed_tools=["weatherForecast"]
        )
        
        # Assert
        assert "Seattle" in response.generated_text
        assert "65" in response.generated_text
        assert "Sunny" in response.generated_text
        assert "Rain" in response.generated_text
        assert len(response.tool_calls) == 1
        assert response.tool_calls[0].tool_name == "weatherForecast"

Testiranje zmogljivosti

1. Testiranje obremenitve

Preverite, koliko sočasnih zahtev lahko obravnava vaš MCP strežnik:

[Fact]
public async Task McpServer_HandlesHighConcurrency()
{
    // Arrange
    var server = new McpServer(
        name: "TestServer",
        version: "1.0",
        maxConcurrentRequests: 100
    );
    
    server.RegisterTool(new FastExecutingTool());
    await server.StartAsync();
    
    var client = new McpClient("http://localhost:5000");
    
    // Act
    var tasks = new List<Task<McpResponse>>();
    for (int i = 0; i < 1000; i++)
    {
        tasks.Add(client.ExecuteToolAsync("fastTool", new { iteration = i }));
    }
    
    var results = await Task.WhenAll(tasks);
    
    // Assert
    Assert.Equal(1000, results.Length);
    Assert.All(results, r => Assert.NotNull(r));
}

2. Testiranje stresa

Preizkusite sistem pod ekstremno obremenitvijo:

@Test
public void testServerUnderStress() {
    int maxUsers = 1000;
    int rampUpTimeSeconds = 60;
    int testDurationSeconds = 300;
    
    // Set up JMeter for stress testing
    StandardJMeterEngine jmeter = new StandardJMeterEngine();
    
    // Configure JMeter test plan
    HashTree testPlanTree = new HashTree();
    
    // Create test plan, thread group, samplers, etc.
    TestPlan testPlan = new TestPlan("MCP Server Stress Test");
    testPlanTree.add(testPlan);
    
    ThreadGroup threadGroup = new ThreadGroup();
    threadGroup.setNumThreads(maxUsers);
    threadGroup.setRampUp(rampUpTimeSeconds);
    threadGroup.setScheduler(true);
    threadGroup.setDuration(testDurationSeconds);
    
    testPlanTree.add(threadGroup);
    
    // Add HTTP sampler for tool execution
    HTTPSampler toolExecutionSampler = new HTTPSampler();
    toolExecutionSampler.setDomain("localhost");
    toolExecutionSampler.setPort(5000);
    toolExecutionSampler.setPath("/mcp/execute");
    toolExecutionSampler.setMethod("POST");
    toolExecutionSampler.addArgument("toolName", "calculator");
    toolExecutionSampler.addArgument("parameters", "{\"operation\":\"add\",\"a\":5,\"b\":7}");
    
    threadGroup.add(toolExecutionSampler);
    
    // Add listeners
    SummaryReport summaryReport = new SummaryReport();
    threadGroup.add(summaryReport);
    
    // Run test
    jmeter.configure(testPlanTree);
    jmeter.run();
    
    // Validate results
    assertEquals(0, summaryReport.getErrorCount());
    assertTrue(summaryReport.getAverage() < 200); // Average response time < 200ms
    assertTrue(summaryReport.getPercentile(90.0) < 500); // 90th percentile < 500ms
}

3. Spremljanje in profiliranje

Nastavite spremljanje za dolgoročno analizo zmogljivosti:

# Configure monitoring for an MCP server
def configure_monitoring(server):
    # Set up Prometheus metrics
    prometheus_metrics = {
        "request_count": Counter("mcp_requests_total", "Total MCP requests"),
        "request_latency": Histogram(
            "mcp_request_duration_seconds", 
            "Request duration in seconds",
            buckets=[0.01, 0.05, 0.1, 0.5, 1.0, 2.5, 5.0, 10.0]
        ),
        "tool_execution_count": Counter(
            "mcp_tool_executions_total", 
            "Tool execution count",
            labelnames=["tool_name"]
        ),
        "tool_execution_latency": Histogram(
            "mcp_tool_duration_seconds", 
            "Tool execution duration in seconds",
            labelnames=["tool_name"],
            buckets=[0.01, 0.05, 0.1, 0.5, 1.0, 2.5, 5.0, 10.0]
        ),
        "tool_errors": Counter(
            "mcp_tool_errors_total",
            "Tool execution errors",
            labelnames=["tool_name", "error_type"]
        )
    }
    
    # Add middleware for timing and recording metrics
    server.add_middleware(PrometheusMiddleware(prometheus_metrics))
    
    # Expose metrics endpoint
    @server.router.get("/metrics")
    async def metrics():
        return generate_latest()
    
    return server

Oblikovni vzorci delovnih tokov MCP

Dobro oblikovani MCP delovni tokovi izboljšujejo učinkovitost, zanesljivost in vzdržljivost. Tukaj so ključni vzorci, ki jih je treba upoštevati:

1. Vzorec verige orodij

Povežite več orodij v zaporedju, kjer izhod vsakega orodja postane vhod za naslednje:

# Python Chain of Tools implementation
class ChainWorkflow:
    def __init__(self, tools_chain):
        self.tools_chain = tools_chain  # List of tool names to execute in sequence
    
    async def execute(self, mcp_client, initial_input):
        current_result = initial_input
        all_results = {"input": initial_input}
        
        for tool_name in self.tools_chain:
            # Execute each tool in the chain, passing previous result
            response = await mcp_client.execute_tool(tool_name, current_result)
            
            # Store result and use as input for next tool
            all_results[tool_name] = response.result
            current_result = response.result
        
        return {
            "final_result": current_result,
            "all_results": all_results
        }

# Example usage
data_processing_chain = ChainWorkflow([
    "dataFetch",
    "dataCleaner",
    "dataAnalyzer",
    "dataVisualizer"
])

result = await data_processing_chain.execute(
    mcp_client,
    {"source": "sales_database", "table": "transactions"}
)

2. Vzorec dispečerja

Uporabite osrednje orodje, ki usmerja k specializiranim orodjem na podlagi vnosa:

public class ContentDispatcherTool : IMcpTool
{
    private readonly IMcpClient _mcpClient;
    
    public ContentDispatcherTool(IMcpClient mcpClient)
    {
        _mcpClient = mcpClient;
    }
    
    public string Name => "contentProcessor";
    public string Description => "Processes content of various types";
    
    public object GetSchema()
    {
        return new {
            type = "object",
            properties = new {
                content = new { type = "string" },
                contentType = new { 
                    type = "string",
                    enum = new[] { "text", "html", "markdown", "csv", "code" }
                },
                operation = new { 
                    type = "string",
                    enum = new[] { "summarize", "analyze", "extract", "convert" }
                }
            },
            required = new[] { "content", "contentType", "operation" }
        };
    }
    
    public async Task<ToolResponse> ExecuteAsync(ToolRequest request)
    {
        var content = request.Parameters.GetProperty("content").GetString();
        var contentType = request.Parameters.GetProperty("contentType").GetString();
        var operation = request.Parameters.GetProperty("operation").GetString();
        
        // Determine which specialized tool to use
        string targetTool = DetermineTargetTool(contentType, operation);
        
        // Forward to the specialized tool
        var specializedResponse = await _mcpClient.ExecuteToolAsync(
            targetTool,
            new { content, options = GetOptionsForTool(targetTool, operation) }
        );
        
        return new ToolResponse { Result = specializedResponse.Result };
    }
    
    private string DetermineTargetTool(string contentType, string operation)
    {
        return (contentType, operation) switch
        {
            ("text", "summarize") => "textSummarizer",
            ("text", "analyze") => "textAnalyzer",
            ("html", _) => "htmlProcessor",
            ("markdown", _) => "markdownProcessor",
            ("csv", _) => "csvProcessor",
            ("code", _) => "codeAnalyzer",
            _ => throw new ToolExecutionException($"No tool available for {contentType}/{operation}")
        };
    }
    
    private object GetOptionsForTool(string toolName, string operation)
    {
        // Return appropriate options for each specialized tool
        return toolName switch
        {
            "textSummarizer" => new { length = "medium" },
            "htmlProcessor" => new { cleanUp = true, operation },
            // Options for other tools...
            _ => new { }
        };
    }
}

3. Vzorec vzporedne obdelave

Izvedite več orodij hkrati za učinkovitost:

public class ParallelDataProcessingWorkflow {
    private final McpClient mcpClient;
    
    public ParallelDataProcessingWorkflow(McpClient mcpClient) {
        this.mcpClient = mcpClient;
    }
    
    public WorkflowResult execute(String datasetId) {
        // Step 1: Fetch dataset metadata (synchronous)
        ToolResponse metadataResponse = mcpClient.executeTool("datasetMetadata", 
            Map.of("datasetId", datasetId));
        
        // Step 2: Launch multiple analyses in parallel
        CompletableFuture<ToolResponse> statisticalAnalysis = CompletableFuture.supplyAsync(() ->
            mcpClient.executeTool("statisticalAnalysis", Map.of(
                "datasetId", datasetId,
                "type", "comprehensive"
            ))
        );
        
        CompletableFuture<ToolResponse> correlationAnalysis = CompletableFuture.supplyAsync(() ->
            mcpClient.executeTool("correlationAnalysis", Map.of(
                "datasetId", datasetId,
                "method", "pearson"
            ))
        );
        
        CompletableFuture<ToolResponse> outlierDetection = CompletableFuture.supplyAsync(() ->
            mcpClient.executeTool("outlierDetection", Map.of(
                "datasetId", datasetId,
                "sensitivity", "medium"
            ))
        );
        
        // Wait for all parallel tasks to complete
        CompletableFuture<Void> allAnalyses = CompletableFuture.allOf(
            statisticalAnalysis, correlationAnalysis, outlierDetection
        );
        
        allAnalyses.join();  // Wait for completion
        
        // Step 3: Combine results
        Map<String, Object> combinedResults = new HashMap<>();
        combinedResults.put("metadata", metadataResponse.getResult());
        combinedResults.put("statistics", statisticalAnalysis.join().getResult());
        combinedResults.put("correlations", correlationAnalysis.join().getResult());
        combinedResults.put("outliers", outlierDetection.join().getResult());
        
        // Step 4: Generate summary report
        ToolResponse summaryResponse = mcpClient.executeTool("reportGenerator", 
            Map.of("analysisResults", combinedResults));
        
        // Return complete workflow result
        WorkflowResult result = new WorkflowResult();
        result.setDatasetId(datasetId);
        result.setAnalysisResults(combinedResults);
        result.setSummaryReport(summaryResponse.getResult());
        
        return result;
    }
}

4. Vzorec okrevanja po napakah

Implementirajte prijazne rešitve za neuspehe orodij:

class ResilientWorkflow:
    def __init__(self, mcp_client):
        self.client = mcp_client
    
    async def execute_with_fallback(self, primary_tool, fallback_tool, parameters):
        try:
            # Try primary tool first
            response = await self.client.execute_tool(primary_tool, parameters)
            return {
                "result": response.result,
                "source": "primary",
                "tool": primary_tool
            }
        except ToolExecutionException as e:
            # Log the failure
            logging.warning(f"Primary tool '{primary_tool}' failed: {str(e)}")
            
            # Fall back to secondary tool
            try:
                # Might need to transform parameters for fallback tool
                fallback_params = self._adapt_parameters(parameters, primary_tool, fallback_tool)
                
                response = await self.client.execute_tool(fallback_tool, fallback_params)
                return {
                    "result": response.result,
                    "source": "fallback",
                    "tool": fallback_tool,
                    "primaryError": str(e)
                }
            except ToolExecutionException as fallback_error:
                # Both tools failed
                logging.error(f"Both primary and fallback tools failed. Fallback error: {str(fallback_error)}")
                raise WorkflowExecutionException(
                    f"Workflow failed: primary error: {str(e)}; fallback error: {str(fallback_error)}"
                )
    
    def _adapt_parameters(self, params, from_tool, to_tool):
        """Adapt parameters between different tools if needed"""
        # This implementation would depend on the specific tools
        # For this example, we'll just return the original parameters
        return params

# Example usage
async def get_weather(workflow, location):
    return await workflow.execute_with_fallback(
        "premiumWeatherService",  # Primary (paid) weather API
        "basicWeatherService",    # Fallback (free) weather API
        {"location": location}
    )

5. Vzorec sestavljanja delovnih tokov

Zgradite kompleksne delovne tokove z združevanjem enostavnejših:

public class CompositeWorkflow : IWorkflow
{
    private readonly List<IWorkflow> _workflows;
    
    public CompositeWorkflow(IEnumerable<IWorkflow> workflows)
    {
        _workflows = new List<IWorkflow>(workflows);
    }
    
    public async Task<WorkflowResult> ExecuteAsync(WorkflowContext context)
    {
        var results = new Dictionary<string, object>();
        
        foreach (var workflow in _workflows)
        {
            var workflowResult = await workflow.ExecuteAsync(context);
            
            // Store each workflow's result
            results[workflow.Name] = workflowResult;
            
            // Update context with the result for the next workflow
            context = context.WithResult(workflow.Name, workflowResult);
        }
        
        return new WorkflowResult(results);
    }
    
    public string Name => "CompositeWorkflow";
    public string Description => "Executes multiple workflows in sequence";
}

// Example usage
var documentWorkflow = new CompositeWorkflow(new IWorkflow[] {
    new DocumentFetchWorkflow(),
    new DocumentProcessingWorkflow(),
    new InsightGenerationWorkflow(),
    new ReportGenerationWorkflow()
});

var result = await documentWorkflow.ExecuteAsync(new WorkflowContext {
    Parameters = new { documentId = "12345" }
});

Testiranje MCP strežnikov: najboljše prakse in vrhunski nasveti

Pregled

Testiranje je ključni vidik razvoja zanesljivih, visokokakovostnih MCP strežnikov. Ta vodič ponuja celovite najboljše prakse in nasvete za testiranje vaših MCP strežnikov skozi celoten življenjski cikel razvoja, od enotnih testov do integracijskih testov in preverjanja od konca do konca.

Zakaj je testiranje pomembno za MCP strežnike

MCP strežniki služijo kot ključna povezava med AI modeli in odjemalskimi aplikacijami. Temeljito testiranje zagotavlja:

  • Zanesljivost v proizvodnih okoljih
  • Natančno obravnavanje zahtev in odgovorov
  • Pravilno implementacijo MCP specifikacij
  • Odpornost proti napakam in robnim primerom
  • Dosledno zmogljivost pri različnih obremenitvah

Enotno testiranje za MCP strežnike

Enotno testiranje (Temelj)

Enotni testi preverjajo posamezne komponente vašega MCP strežnika v izolaciji.

Kaj testirati

  1. Upravljalci virov: Preverite logiko vsakega upravljalca virov neodvisno
  2. Implementacije orodij: Preverite obnašanje orodij z različnimi vnosi
  3. Predloge navodil: Zagotovite pravilno upodabljanje predlog navodil
  4. Validacija shem: Testirajte logiko validacije parametrov
  5. Ravnanje z napakami: Preverite odgovore na napake za neveljavne vnose

Najboljše prakse za enotno testiranje

// Example unit test for a calculator tool in C#
[Fact]
public async Task CalculatorTool_Add_ReturnsCorrectSum()
{
    // Arrange
    var calculator = new CalculatorTool();
    var parameters = new Dictionary<string, object>
    {
        ["operation"] = "add",
        ["a"] = 5,
        ["b"] = 7
    };
    
    // Act
    var response = await calculator.ExecuteAsync(parameters);
    var result = JsonSerializer.Deserialize<CalculationResult>(response.Content[0].ToString());
    
    // Assert
    Assert.Equal(12, result.Value);
}
# Example unit test for a calculator tool in Python
def test_calculator_tool_add():
    # Arrange
    calculator = CalculatorTool()
    parameters = {
        "operation": "add",
        "a": 5,
        "b": 7
    }
    
    # Act
    response = calculator.execute(parameters)
    result = json.loads(response.content[0].text)
    
    # Assert
    assert result["value"] == 12

Integracijsko testiranje (Srednji sloj)

Integracijski testi preverjajo interakcije med komponentami vašega MCP strežnika.

Kaj testirati

  1. Inicializacija strežnika: Preverite zagon strežnika z različnimi konfiguracijami
  2. Registracija poti: Preverite pravilno registracijo vseh končnih točk
  3. Obdelava zahtevkov: Preverite celoten cikel zahtevek-odgovor
  4. Propagacija napak: Zagotovite pravilno ravnanje z napakami med komponentami
  5. Avtentikacija in avtorizacija: Preverite varnostne mehanizme

Najboljše prakse za integracijsko testiranje

// Example integration test for MCP server in C#
[Fact]
public async Task Server_ProcessToolRequest_ReturnsValidResponse()
{
    // Arrange
    var server = new McpServer();
    server.RegisterTool(new CalculatorTool());
    await server.StartAsync();
    
    var request = new McpRequest
    {
        Tool = "calculator",
        Parameters = new Dictionary<string, object>
        {
            ["operation"] = "multiply",
            ["a"] = 6,
            ["b"] = 7
        }
    };
    
    // Act
    var response = await server.ProcessRequestAsync(request);
    
    // Assert
    Assert.NotNull(response);
    Assert.Equal(McpStatusCodes.Success, response.StatusCode);
    // Additional assertions for response content
    
    // Cleanup
    await server.StopAsync();
}

Testiranje od konca do konca (Zgornji sloj)

Testi od konca do konca preverjajo celotno obnašanje sistema od odjemalca do strežnika.

Kaj testirati

  1. Komunikacija odjemalec-strežnik: Preverite celotne cikle zahtevek-odgovor
  2. Resnični odjemalski SDK-ji: Preverite z dejanskimi implementacijami odjemalcev
  3. Zmogljivost pod obremenitvijo: Preverite obnašanje pri več sočasnih zahtevah
  4. Okrevanje po napakah: Preverite okrevanje sistema po neuspehih
  5. Dolgotrajne operacije: Preverite ravnanje s pretakanjem in dolgimi operacijami

Najboljše prakse za E2E testiranje

// Example E2E test with a client in TypeScript
describe('MCP Server E2E Tests', () => {
  let client: McpClient;
  
  beforeAll(async () => {
    // Start server in test environment
    await startTestServer();
    client = new McpClient('http://localhost:5000');
  });
  
  afterAll(async () => {
    await stopTestServer();
  });
  
  test('Client can invoke calculator tool and get correct result', async () => {
    // Act
    const response = await client.invokeToolAsync('calculator', {
      operation: 'divide',
      a: 20,
      b: 4
    });
    
    // Assert
    expect(response.statusCode).toBe(200);
    expect(response.content[0].text).toContain('5');
  });
});

Strategije nadomestkov za testiranje MCP

Nadomeščanje je bistveno za izolacijo komponent med testiranjem.

Komponente za nadomeščanje

  1. Zunanji AI modeli: Nadomestite odzive modelov za predvidljivo testiranje
  2. Zunanje storitve: Nadomestite odvisnosti API (podatkovne baze, storitve tretjih oseb)
  3. Storitve avtentikacije: Nadomestite ponudnike identitet
  4. Ponudniki virov: Nadomestite drage upravljalce virov

Primer: Nadomeščanje odziva AI modela

// C# example with Moq
var mockModel = new Mock<ILanguageModel>();
mockModel
    .Setup(m => m.GenerateResponseAsync(
        It.IsAny<string>(),
        It.IsAny<McpRequestContext>()))
    .ReturnsAsync(new ModelResponse { 
        Text = "Mocked model response",
        FinishReason = FinishReason.Completed
    });

var server = new McpServer(modelClient: mockModel.Object);
# Python example with unittest.mock
@patch('mcp_server.models.OpenAIModel')
def test_with_mock_model(mock_model):
    # Configure mock
    mock_model.return_value.generate_response.return_value = {
        "text": "Mocked model response",
        "finish_reason": "completed"
    }
    
    # Use mock in test
    server = McpServer(model_client=mock_model)
    # Continue with test

Testiranje zmogljivosti

Testiranje zmogljivosti je ključno za produkcijske MCP strežnike.

Kaj meriti

  1. Latenca: Čas odziva za zahteve
  2. Prepustnost: Zahteve, obravnavane na sekundo
  3. Izraba virov: Uporaba CPU, pomnilnika, omrežja
  4. Ravnanje s sočasnostjo: Obnašanje pod vzporednimi zahtevami
  5. Značilnosti skaliranja: Zmogljivost, ko se obremenitev povečuje

Orodja za testiranje zmogljivosti

  • k6: Orodje za testiranje obremenitve odprte kode
  • JMeter: Celovito testiranje zmogljivosti
  • Locust: Testiranje obremenitve, osnovano na Pythonu
  • Azure Load Testing: Testiranje zmogljivosti v oblaku

Primer: Osnovni test obremenitve z k6

// k6 script for load testing MCP server
import http from 'k6/http';
import { check, sleep } from 'k6';

export const options = {
  vus: 10,  // 10 virtual users
  duration: '30s',
};

export default function () {
  const payload = JSON.stringify({
    tool: 'calculator',
    parameters: {
      operation: 'add',
      a: Math.floor(Math.random() * 100),
      b: Math.floor(Math.random() * 100)
    }
  });

  const params = {
    headers: {
      'Content-Type': 'application/json',
      'Authorization': 'Bearer test-token'
    },
  };

  const res = http.post('http://localhost:5000/api/tools/invoke', payload, params);
  
  check(res, {
    'status is 200': (r) => r.status === 200,
    'response time < 500ms': (r) => r.timings.duration < 500,
  });
  
  sleep(1);
}

Avtomatizacija testiranja za MCP strežnike

Avtomatizacija testov zagotavlja dosledno kakovost in hitrejše povratne zanke.

Integracija CI/CD

  1. Izvajajte enotne teste ob potegih zahtev: Zagotovite, da spremembe kode ne pokvarijo obstoječe funkcionalnosti
  2. Integracijski testi v fazi testiranja: Izvajajte integracijske teste v predprodukcijskih okoljih
  3. Referenčne vrednosti zmogljivosti: Vzdržujte referenčne vrednosti zmogljivosti za zaznavanje regresij
  4. Varnostno skeniranje: Avtomatizirajte varnostno testiranje kot del pipeline-a

Primer CI pipeline (GitHub Actions)

name: MCP Server Tests

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  test:
    runs-on: ubuntu-latest
    
    steps:
    - uses: actions/checkout@v2
    
    - name: Set up Runtime
      uses: actions/setup-dotnet@v1
      with:
        dotnet-version: '8.0.x'
    
    - name: Restore dependencies
      run: dotnet restore
    
    - name: Build
      run: dotnet build --no-restore
    
    - name: Unit Tests
      run: dotnet test --no-build --filter Category=Unit
    
    - name: Integration Tests
      run: dotnet test --no-build --filter Category=Integration
      
    - name: Performance Tests
      run: dotnet run --project tests/PerformanceTests/PerformanceTests.csproj

Testiranje skladnosti s specifikacijo MCP

Preverite, ali vaš strežnik pravilno implementira specifikacijo MCP.

Ključna področja skladnosti

  1. API končne točke: Preverite zahtevane končne točke (/resources, /tools, itd.)
  2. Format zahtevkov/odgovorov: Preverite skladnost s shemo
  3. Kode napak: Preverite pravilne statusne kode za različne scenarije
  4. Vrste vsebine: Preverite ravnanje z različnimi vrstami vsebin
  5. Tok avtentikacije: Preverite skladne mehanizme za avtentikacijo

Skladen testni nabor

[Fact]
public async Task Server_ResourceEndpoint_ReturnsCorrectSchema()
{
    // Arrange
    var client = new HttpClient();
    client.DefaultRequestHeaders.Add("Authorization", "Bearer test-token");
    
    // Act
    var response = await client.GetAsync("http://localhost:5000/api/resources");
    var content = await response.Content.ReadAsStringAsync();
    var resources = JsonSerializer.Deserialize<ResourceList>(content);
    
    // Assert
    Assert.Equal(HttpStatusCode.OK, response.StatusCode);
    Assert.NotNull(resources);
    Assert.All(resources.Resources, resource => 
    {
        Assert.NotNull(resource.Id);
        Assert.NotNull(resource.Type);
        // Additional schema validation
    });
}

Top 10 nasvetov za učinkovito testiranje MCP strežnikov

  1. Testirajte definicije orodij ločeno: Preverite definicije shem neodvisno od logike orodij
  2. Uporabite parametrične teste: Preverite orodja z različnimi vnosi, vključno z robnimi primeri
  3. Preverite odgovore na napake: Preverite ustrezno ravnanje z napakami za vse možne pogoje napak
  4. Preverite logiko avtorizacije: Zagotovite pravilno kontrolo dostopa za različne uporabniške vloge
  5. Spremljajte pokritost testov: Ciljajte na visoko pokritost kritične poti kode
  6. Testirajte pretakanje odgovorov: Preverite pravilno ravnanje s pretočno vsebino
  7. Simulirajte omrežne težave: Preverite obnašanje v slabih omrežnih pogojih
  8. Preverite omejitve virov: Preverite obnašanje pri doseganju kvot ali omejitev hitrosti
  9. Avtomatizirajte regresijske teste: Zgradite nabor, ki se izvaja ob vsaki spremembi kode
  10. Dokumentirajte testne primere: Vzdržujte jasno dokumentacijo testnih scenarijev

Pogoste pasti pri testiranju

  • Preveliko zanašanje na testiranje srečne poti: Poskrbite, da temeljito preizkusite primere napak
  • Ignoriranje testiranja zmogljivosti: Identificirajte ozka grla, preden vplivajo na produkcijo
  • Testiranje samo v izolaciji: Združite enotne, integracijske in E2E teste
  • Nepopolna pokritost API: Zagotovite, da so testirane vse končne točke in funkcije
  • Nedosledna testna okolja: Uporabite kontejnere za zagotavljanje doslednih testnih okolij

Zaključek

Celovita strategija testiranja je bistvena za razvoj zanesljivih, visokokakovostnih MCP strežnikov. Z implementacijo najboljših praks in nasvetov, opisanih v tem vodiču, lahko zagotovite, da vaše MCP implementacije izpolnjujejo najvišje standarde kakovosti, zanesljivosti in zmogljivosti.

Ključne ugotovitve

  1. Oblikovanje orodij: Upoštevajte načelo enotne odgovornosti, uporabite injekcijo odvisnosti in oblikujte za združljivost
  2. Oblikovanje shem: Ustvarite jasne, dobro dokumentirane sheme s pravilnimi omejitvami validacije
  3. Ravnanje z napakami: Implementirajte prijazno ravnanje z napakami, strukturirane odgovore na napake in logiko ponovnega poskusa
  4. Zmogljivost: Uporabite predpom

Omejitev odgovornosti: Ta dokument je bil preveden s pomočjo storitve AI prevajanja Co-op Translator. Čeprav si prizadevamo za natančnost, vas prosimo, da se zavedate, da lahko avtomatizirani prevodi vsebujejo napake ali netočnosti. Izvirni dokument v njegovem maternem jeziku je treba obravnavati kot avtoritativni vir. Za kritične informacije je priporočljiv profesionalni človeški prevod. Ne odgovarjamo za kakršne koli nesporazume ali napačne interpretacije, ki izhajajo iz uporabe tega prevoda.