V3 MCP Optimization 精选
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.
安装方式
cp -r .claude/skills/v3-mcp-optimization ~/.claude/skills/v3-mcp-optimization把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/
/plugin marketplace add ruvnet/RuView⚠️ 该命令形态随客户端版本变化,仅在检测到 .claude-plugin/marketplace.json 时展示;不可用时请用「目录复制」。
https://raw.githubusercontent.com/ruvnet/RuView/a71634ae8a606bba5463489450c69e8b42de114e/.claude/skills/v3-mcp-optimization/SKILL.md下载后另存为 ~/.claude/skills/v3-mcp-optimization/SKILL.md。链接锁定采集时的 commit,内容与本站展示一致。
整仓一次性获取:git clone --depth 1 https://github.com/ruvnet/RuView.git
依赖与权限
- 无需 API Key
- 需要联网访问外部服务
- 无外部命令依赖
- 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
SKILL.md 正文
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
# Initialize MCP optimization analysis
Task("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
// src/core/mcp/mcp-server.ts
import { 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
// src/core/mcp/connection-pool.ts
interface 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
// src/core/mcp/fast-tool-registry.ts
interface 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
// src/core/mcp/load-balancer.ts
interface 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
// src/core/mcp/optimized-transport.ts
export 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
// src/core/mcp/metrics.ts
interface 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
// src/core/mcp/tool-precompiler.ts
export 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
// src/core/mcp/multi-level-cache.ts
export 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
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 MCPv3-performance-optimization- Overall performance optimizationv3-swarm-coordination- MCP integration with swarm coordinationv3-memory-unification- Memory sharing via MCP tools
Usage Examples
Complete MCP Optimization
# Full MCP server optimization
Task("MCP optimization implementation",
"Implement all MCP performance optimizations with monitoring",
"mcp-specialist")
Specific Optimization
# Connection pool optimization
Task("MCP connection pooling",
"Implement advanced connection pooling with health monitoring",
"mcp-specialist")质量与来源
- 所属仓库
- ruvnet/RuView
- 仓库星标
- 9.8 万
- 最近更新
- 今天
- 采集时间
- 今天
- commit
- a71634ae8a60
- 内容指纹
- sha256:309969c33ee3a25
- 文件路径
- .claude/skills/v3-mcp-optimization/SKILL.md
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