V3 MCP Optimization

ruvnet/ruflo/v3/@claude-flow/cli/.claude/skills/v3-mcp-optimization

作者 ruvnet58e0ae7e14e68aab45a4127d6f42f567bbcfb328無授權條款74K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫今天更新

MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.

AI 產生的概覽

透過連線池、負載平衡、工具登錄索引與效能監控來最佳化 claude-flow v3 MCP 伺服器。

功能
此技能為最佳化 claude-flow v3 的 Model Context Protocol 伺服器提供指引與 TypeScript 參考實作。內容涵蓋含預熱與健康檢查的連線池、以雜湊為基礎的 O(1) 工具登錄(含模糊比對與快取)、多伺服器執行個體的負載平衡策略、傳輸層批次處理與壓縮、多層快取,以及即時指標收集。目標是 p95 回應時間低於 100 毫秒、更快的啟動速度、更高的連線池命中率與更低的記憶體用量。
適用情境
當以 claude-flow v3 為基礎的 MCP 伺服器啟動緩慢、每次請求的連線負擔過高,或需要更快的工具查詢與更高輸送量時使用。適合傳輸效能、連線重用、負載分配與 MCP 效能監控相關工作。
執行需求
需要以 TypeScript 撰寫的 claude-flow v3 MCP 伺服器程式碼庫、@modelcontextprotocol/sdk 套件,以及支援 performance.now 與 gzipSync 的 Node.js 執行環境。此技能不附帶指令碼,僅為說明文件與程式碼範例。

V3 MCP Optimization

What This Skill Does

Optimizes claude-flow v3 MCP (Model Context Protocol) server implementation with advanced transport layer optimizations, connection pooling, load balancing, and comprehensive performance monitoring to achieve sub-100ms response times.

Quick Start

bash
# Initialize MCP optimization analysisTask("MCP architecture", "Analyze current MCP server performance and bottlenecks", "mcp-specialist")
# Optimization implementation (parallel)Task("Connection pooling", "Implement MCP connection pooling and reuse", "mcp-specialist")Task("Load balancing", "Add dynamic load balancing for MCP tools", "mcp-specialist")Task("Transport optimization", "Optimize transport layer performance", "mcp-specialist")

MCP Performance Architecture

Current State Analysis

Current MCP Issues:├── Cold Start Latency: ~1.8s MCP server init├── Connection Overhead: New connection per request├── Tool Registry: Linear search O(n) for 213+ tools├── Transport Layer: No connection reuse└── Memory Usage: No cleanup of idle connections
Target Performance:├── Startup Time: <400ms (4.5x improvement)├── Tool Lookup: <5ms (O(1) hash table)├── Connection Reuse: 90%+ connection pool hits├── Response Time: <100ms p95└── Memory Efficiency: 50% reduction

MCP Server Architecture

typescript
// src/core/mcp/mcp-server.tsimport { Server } from '@modelcontextprotocol/sdk/server/index.js';import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
interface OptimizedMCPConfig {  // Connection pooling  maxConnections: number;  idleTimeoutMs: number;  connectionReuseEnabled: boolean;
  // Tool registry  toolCacheEnabled: boolean;  toolIndexType: 'hash' | 'trie';
  // Performance  requestTimeoutMs: number;  batchingEnabled: boolean;  compressionEnabled: boolean;
  // Monitoring  metricsEnabled: boolean;  healthCheckIntervalMs: number;}
export class OptimizedMCPServer {  private server: Server;  private connectionPool: ConnectionPool;  private toolRegistry: FastToolRegistry;  private loadBalancer: MCPLoadBalancer;  private metrics: MCPMetrics;
  constructor(config: OptimizedMCPConfig) {    this.server = new Server({      name: 'claude-flow-v3',      version: '3.0.0'    }, {      capabilities: {        tools: { listChanged: true },        resources: { subscribe: true, listChanged: true },        prompts: { listChanged: true }      }    });
    this.connectionPool = new ConnectionPool(config);    this.toolRegistry = new FastToolRegistry(config.toolIndexType);    this.loadBalancer = new MCPLoadBalancer();    this.metrics = new MCPMetrics(config.metricsEnabled);  }
  async start(): Promise<void> {    // Pre-warm connection pool    await this.connectionPool.preWarm();
    // Pre-build tool index    await this.toolRegistry.buildIndex();
    // Setup request handlers with optimizations    this.setupOptimizedHandlers();
    // Start health monitoring    this.startHealthMonitoring();
    // Start server    const transport = new StdioServerTransport();    await this.server.connect(transport);
    this.metrics.recordStartup();  }}

Connection Pool Implementation

Advanced Connection Pooling

typescript
// src/core/mcp/connection-pool.tsinterface PooledConnection {  id: string;  connection: MCPConnection;  lastUsed: number;  usageCount: number;  isHealthy: boolean;}
export class ConnectionPool {  private pool: Map<string, PooledConnection> = new Map();  private readonly config: ConnectionPoolConfig;  private healthChecker: HealthChecker;
  constructor(config: ConnectionPoolConfig) {    this.config = {      maxConnections: 50,      minConnections: 5,      idleTimeoutMs: 300000, // 5 minutes      maxUsageCount: 1000,      healthCheckIntervalMs: 30000,      ...config    };
    this.healthChecker = new HealthChecker(this.config.healthCheckIntervalMs);  }
  async getConnection(endpoint: string): Promise<MCPConnection> {    const start = performance.now();
    // Try to get from pool first    const pooled = this.findAvailableConnection(endpoint);    if (pooled) {      pooled.lastUsed = Date.now();      pooled.usageCount++;
      this.recordMetric('pool_hit', performance.now() - start);      return pooled.connection;    }
    // Check pool capacity    if (this.pool.size >= this.config.maxConnections) {      await this.evictLeastUsedConnection();    }
    // Create new connection    const connection = await this.createConnection(endpoint);    const pooledConn: PooledConnection = {      id: this.generateConnectionId(),      connection,      lastUsed: Date.now(),      usageCount: 1,      isHealthy: true    };
    this.pool.set(pooledConn.id, pooledConn);    this.recordMetric('pool_miss', performance.now() - start);
    return connection;  }
  async releaseConnection(connection: MCPConnection): Promise<void> {    // Mark connection as available for reuse    const pooled = this.findConnectionById(connection.id);    if (pooled) {      // Check if connection should be retired      if (pooled.usageCount >= this.config.maxUsageCount) {        await this.removeConnection(pooled.id);      }    }  }
  async preWarm(): Promise<void> {    const connections: Promise<MCPConnection>[] = [];
    for (let i = 0; i < this.config.minConnections; i++) {      connections.push(this.createConnection('default'));    }
    await Promise.all(connections);  }
  private async evictLeastUsedConnection(): Promise<void> {    let oldestConn: PooledConnection | null = null;    let oldestTime = Date.now();
    for (const conn of this.pool.values()) {      if (conn.lastUsed < oldestTime) {        oldestTime = conn.lastUsed;        oldestConn = conn;      }    }
    if (oldestConn) {      await this.removeConnection(oldestConn.id);    }  }
  private findAvailableConnection(endpoint: string): PooledConnection | null {    for (const conn of this.pool.values()) {      if (conn.isHealthy &&          conn.connection.endpoint === endpoint &&          Date.now() - conn.lastUsed < this.config.idleTimeoutMs) {        return conn;      }    }    return null;  }}

Fast Tool Registry

O(1) Tool Lookup Implementation

typescript
// src/core/mcp/fast-tool-registry.tsinterface ToolIndexEntry {  name: string;  handler: ToolHandler;  metadata: ToolMetadata;  usageCount: number;  avgLatencyMs: number;}
export class FastToolRegistry {  private toolIndex: Map<string, ToolIndexEntry> = new Map();  private categoryIndex: Map<string, string[]> = new Map();  private fuzzyMatcher: FuzzyMatcher;  private cache: LRUCache<string, ToolIndexEntry>;
  constructor(indexType: 'hash' | 'trie' = 'hash') {    this.fuzzyMatcher = new FuzzyMatcher();    this.cache = new LRUCache<string, ToolIndexEntry>(1000); // Cache 1000 most used tools  }
  async buildIndex(): Promise<void> {    const start = performance.now();
    // Load all available tools    const tools = await this.loadAllTools();
    // Build hash index for O(1) lookup    for (const tool of tools) {      const entry: ToolIndexEntry = {        name: tool.name,        handler: tool.handler,        metadata: tool.metadata,        usageCount: 0,        avgLatencyMs: 0      };
      this.toolIndex.set(tool.name, entry);
      // Build category index      const category = tool.metadata.category || 'general';      if (!this.categoryIndex.has(category)) {        this.categoryIndex.set(category, []);      }      this.categoryIndex.get(category)!.push(tool.name);    }
    // Build fuzzy search index    await this.fuzzyMatcher.buildIndex(tools.map(t => t.name));
    console.log(`Tool index built in ${(performance.now() - start).toFixed(2)}ms for ${tools.length} tools`);  }
  findTool(name: string): ToolIndexEntry | null {    // Try cache first    const cached = this.cache.get(name);    if (cached) return cached;
    // Try exact match    const exact = this.toolIndex.get(name);    if (exact) {      this.cache.set(name, exact);      return exact;    }
    // Try fuzzy match    const fuzzyMatches = this.fuzzyMatcher.search(name, 1);    if (fuzzyMatches.length > 0) {      const match = this.toolIndex.get(fuzzyMatches[0]);      if (match) {        this.cache.set(name, match);        return match;      }    }
    return null;  }
  findToolsByCategory(category: string): ToolIndexEntry[] {    const toolNames = this.categoryIndex.get(category) || [];    return toolNames      .map(name => this.toolIndex.get(name))      .filter(entry => entry !== undefined) as ToolIndexEntry[];  }
  getMostUsedTools(limit: number = 10): ToolIndexEntry[] {    return Array.from(this.toolIndex.values())      .sort((a, b) => b.usageCount - a.usageCount)      .slice(0, limit);  }
  recordToolUsage(toolName: string, latencyMs: number): void {    const entry = this.toolIndex.get(toolName);    if (entry) {      entry.usageCount++;      // Moving average for latency      entry.avgLatencyMs = (entry.avgLatencyMs + latencyMs) / 2;    }  }}

Load Balancing & Request Distribution

Intelligent Load Balancer

typescript
// src/core/mcp/load-balancer.tsinterface ServerInstance {  id: string;  endpoint: string;  load: number;  responseTime: number;  isHealthy: boolean;  maxConnections: number;  currentConnections: number;}
export class MCPLoadBalancer {  private servers: Map<string, ServerInstance> = new Map();  private routingStrategy: RoutingStrategy = 'least-connections';
  addServer(server: ServerInstance): void {    this.servers.set(server.id, server);  }
  selectServer(toolCategory?: string): ServerInstance | null {    const healthyServers = Array.from(this.servers.values())      .filter(server => server.isHealthy);
    if (healthyServers.length === 0) return null;
    switch (this.routingStrategy) {      case 'round-robin':        return this.roundRobinSelection(healthyServers);
      case 'least-connections':        return this.leastConnectionsSelection(healthyServers);
      case 'response-time':        return this.responseTimeSelection(healthyServers);
      case 'weighted':        return this.weightedSelection(healthyServers, toolCategory);
      default:        return healthyServers[0];    }  }
  private leastConnectionsSelection(servers: ServerInstance[]): ServerInstance {    return servers.reduce((least, current) =>      current.currentConnections < least.currentConnections ? current : least    );  }
  private responseTimeSelection(servers: ServerInstance[]): ServerInstance {    return servers.reduce((fastest, current) =>      current.responseTime < fastest.responseTime ? current : fastest    );  }
  private weightedSelection(servers: ServerInstance[], category?: string): ServerInstance {    // Prefer servers with lower load and better response time    const scored = servers.map(server => ({      server,      score: this.calculateServerScore(server, category)    }));
    scored.sort((a, b) => b.score - a.score);    return scored[0].server;  }
  private calculateServerScore(server: ServerInstance, category?: string): number {    const loadFactor = 1 - (server.currentConnections / server.maxConnections);    const responseFactor = 1 / (server.responseTime + 1);    const categoryBonus = this.getCategoryBonus(server, category);
    return loadFactor * 0.4 + responseFactor * 0.4 + categoryBonus * 0.2;  }
  updateServerMetrics(serverId: string, metrics: Partial<ServerInstance>): void {    const server = this.servers.get(serverId);    if (server) {      Object.assign(server, metrics);    }  }}

Transport Layer Optimization

High-Performance Transport

typescript
// src/core/mcp/optimized-transport.tsexport class OptimizedTransport {  private compression: boolean = true;  private batching: boolean = true;  private batchBuffer: MCPMessage[] = [];  private batchTimeout: NodeJS.Timeout | null = null;
  constructor(private config: TransportConfig) {}
  async send(message: MCPMessage): Promise<void> {    if (this.batching && this.canBatch(message)) {      this.addToBatch(message);      return;    }
    await this.sendImmediate(message);  }
  private async sendImmediate(message: MCPMessage): Promise<void> {    const start = performance.now();
    // Compress if enabled    const payload = this.compression      ? await this.compress(message)      : message;
    // Send through transport    await this.transport.send(payload);
    // Record metrics    this.recordLatency(performance.now() - start);  }
  private addToBatch(message: MCPMessage): void {    this.batchBuffer.push(message);
    // Start batch timeout if not already running    if (!this.batchTimeout) {      this.batchTimeout = setTimeout(        () => this.flushBatch(),        this.config.batchTimeoutMs || 10      );    }
    // Flush if batch is full    if (this.batchBuffer.length >= this.config.maxBatchSize) {      this.flushBatch();    }  }
  private async flushBatch(): Promise<void> {    if (this.batchBuffer.length === 0) return;
    const batch = this.batchBuffer.splice(0);    this.batchTimeout = null;
    // Send as single batched message    await this.sendImmediate({      type: 'batch',      messages: batch    });  }
  private canBatch(message: MCPMessage): boolean {    // Don't batch urgent messages or responses    return message.type !== 'response' &&           message.priority !== 'high' &&           message.type !== 'error';  }
  private async compress(data: any): Promise<Buffer> {    // Use fast compression for smaller messages    return gzipSync(JSON.stringify(data));  }}

Performance Monitoring

Real-time MCP Metrics

typescript
// src/core/mcp/metrics.tsinterface MCPMetrics {  requestCount: number;  errorCount: number;  avgResponseTime: number;  p95ResponseTime: number;  connectionPoolHits: number;  connectionPoolMisses: number;  toolLookupTime: number;  startupTime: number;}
export class MCPMetricsCollector {  private metrics: MCPMetrics;  private responseTimeBuffer: number[] = [];  private readonly bufferSize = 1000;
  constructor() {    this.metrics = this.createInitialMetrics();  }
  recordRequest(latencyMs: number): void {    this.metrics.requestCount++;    this.updateResponseTimes(latencyMs);  }
  recordError(): void {    this.metrics.errorCount++;  }
  recordConnectionPoolHit(): void {    this.metrics.connectionPoolHits++;  }
  recordConnectionPoolMiss(): void {    this.metrics.connectionPoolMisses++;  }
  recordToolLookup(latencyMs: number): void {    this.metrics.toolLookupTime = this.updateMovingAverage(      this.metrics.toolLookupTime,      latencyMs    );  }
  recordStartup(latencyMs: number): void {    this.metrics.startupTime = latencyMs;  }
  getMetrics(): MCPMetrics {    return { ...this.metrics };  }
  getHealthStatus(): HealthStatus {    const errorRate = this.metrics.errorCount / this.metrics.requestCount;    const poolHitRate = this.metrics.connectionPoolHits /      (this.metrics.connectionPoolHits + this.metrics.connectionPoolMisses);
    return {      status: this.determineHealthStatus(errorRate, poolHitRate),      errorRate,      poolHitRate,      avgResponseTime: this.metrics.avgResponseTime,      p95ResponseTime: this.metrics.p95ResponseTime    };  }
  private updateResponseTimes(latency: number): void {    this.responseTimeBuffer.push(latency);
    if (this.responseTimeBuffer.length > this.bufferSize) {      this.responseTimeBuffer.shift();    }
    this.metrics.avgResponseTime = this.calculateAverage(this.responseTimeBuffer);    this.metrics.p95ResponseTime = this.calculatePercentile(this.responseTimeBuffer, 95);  }
  private calculatePercentile(arr: number[], percentile: number): number {    const sorted = arr.slice().sort((a, b) => a - b);    const index = Math.ceil((percentile / 100) * sorted.length) - 1;    return sorted[index] || 0;  }
  private determineHealthStatus(errorRate: number, poolHitRate: number): 'healthy' | 'warning' | 'critical' {    if (errorRate > 0.1 || poolHitRate < 0.5) return 'critical';    if (errorRate > 0.05 || poolHitRate < 0.7) return 'warning';    return 'healthy';  }}

Tool Registry Optimization

Pre-compiled Tool Index

typescript
// src/core/mcp/tool-precompiler.tsexport class ToolPrecompiler {  async precompileTools(): Promise<CompiledToolRegistry> {    const tools = await this.loadAllTools();
    // Create optimized lookup structures    const nameIndex = new Map<string, Tool>();    const categoryIndex = new Map<string, Tool[]>();    const fuzzyIndex = new Map<string, string[]>();
    for (const tool of tools) {      // Exact name index      nameIndex.set(tool.name, tool);
      // Category index      const category = tool.metadata.category || 'general';      if (!categoryIndex.has(category)) {        categoryIndex.set(category, []);      }      categoryIndex.get(category)!.push(tool);
      // Pre-compute fuzzy variations      const variations = this.generateFuzzyVariations(tool.name);      for (const variation of variations) {        if (!fuzzyIndex.has(variation)) {          fuzzyIndex.set(variation, []);        }        fuzzyIndex.get(variation)!.push(tool.name);      }    }
    return {      nameIndex,      categoryIndex,      fuzzyIndex,      totalTools: tools.length,      compiledAt: new Date()    };  }
  private generateFuzzyVariations(name: string): string[] {    const variations: string[] = [];
    // Common typos and abbreviations    variations.push(name.toLowerCase());    variations.push(name.replace(/[-_]/g, ''));    variations.push(name.replace(/[aeiou]/gi, '')); // Consonants only
    // Add more fuzzy matching logic as needed
    return variations;  }}

Advanced Caching Strategy

Multi-Level Caching

typescript
// src/core/mcp/multi-level-cache.tsexport class MultiLevelCache {  private l1Cache: Map<string, any> = new Map(); // In-memory, fastest  private l2Cache: LRUCache<string, any>; // LRU cache, larger capacity  private l3Cache: DiskCache; // Persistent disk cache
  constructor(config: CacheConfig) {    this.l2Cache = new LRUCache<string, any>({      max: config.l2MaxEntries || 10000,      ttl: config.l2TTL || 300000 // 5 minutes    });
    this.l3Cache = new DiskCache(config.l3Path || './.cache/mcp');  }
  async get(key: string): Promise<any | null> {    // Try L1 cache first (fastest)    if (this.l1Cache.has(key)) {      return this.l1Cache.get(key);    }
    // Try L2 cache    const l2Value = this.l2Cache.get(key);    if (l2Value) {      // Promote to L1      this.l1Cache.set(key, l2Value);      return l2Value;    }
    // Try L3 cache (disk)    const l3Value = await this.l3Cache.get(key);    if (l3Value) {      // Promote to L2 and L1      this.l2Cache.set(key, l3Value);      this.l1Cache.set(key, l3Value);      return l3Value;    }
    return null;  }
  async set(key: string, value: any, options?: CacheOptions): Promise<void> {    // Set in all levels    this.l1Cache.set(key, value);    this.l2Cache.set(key, value);
    if (options?.persistent) {      await this.l3Cache.set(key, value);    }
    // Manage L1 cache size    if (this.l1Cache.size > 1000) {      const firstKey = this.l1Cache.keys().next().value;      this.l1Cache.delete(firstKey);    }  }}

Success Metrics

Performance Targets

  • Startup Time: <400ms MCP server initialization (4.5x improvement)
  • Response Time: <100ms p95 for tool execution
  • Tool Lookup: <5ms average lookup time
  • Connection Pool: >90% hit rate
  • Memory Usage: 50% reduction in idle memory
  • Error Rate: <1% failed requests
  • Throughput: >1000 requests/second

Monitoring Dashboards

typescript
const mcpDashboard = {  metrics: [    'Request latency (p50, p95, p99)',    'Error rate by tool category',    'Connection pool utilization',    'Tool lookup performance',    'Memory usage trends',    'Cache hit rates (L1, L2, L3)'  ],
  alerts: [    'Response time >200ms for 5 minutes',    'Error rate >5% for 1 minute',    'Pool hit rate <70% for 10 minutes',    'Memory usage >500MB for 5 minutes'  ]};

Related V3 Skills

  • v3-core-implementation - Core domain integration with MCP
  • v3-performance-optimization - Overall performance optimization
  • v3-swarm-coordination - MCP integration with swarm coordination
  • v3-memory-unification - Memory sharing via MCP tools

Usage Examples

Complete MCP Optimization

bash
# Full MCP server optimizationTask("MCP optimization implementation",     "Implement all MCP performance optimizations with monitoring",     "mcp-specialist")

Specific Optimization

bash
# Connection pool optimizationTask("MCP connection pooling",     "Implement advanced connection pooling with health monitoring",     "mcp-specialist")

來源與署名

來源:ruvnet/ruflo位於v3/@claude-flow/cli/.claude/skills/v3-mcp-optimization提交58e0ae7

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