V3 MCP Optimization
Skill79k starsChanged 24 days agoMITView on GitHub
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.
27 other projects use a version of this, 4 of them edited.
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Who's talking about ruvnet/ruflo
- Kaya Rezende“Claude Code with RuFlo v3.5: Enterprise AI Orchestration Platform”YouTube · Mar 31, 2026 · 35k views
- Hungry Labs“ruflo: Turn Claude Code into a Swarm of 100 AI Agents”YouTube · May 3, 2026 · 14k views
- Alex Hitt“Ruflo GitHub Setup Guide: Register Claude Flow MCP and Verify Persistent Memory Recall”YouTube · Aug 24, 2026 · 4.5k views
- @BytesAndBricks“Ruflo Explained: Multi-Agent AI Orchestration for Claude Code & Beyond”YouTube · Jun 15, 2026 · 1.8k views
- Kuro“Ruflo - Multi-Agent AI Harness for Claude Code & Codex”YouTube · Jun 6, 2026 · 1.5k views
The biggest 5 of 88 mentions linking to the repository that our crawl found. Each line is their own headline.
See all 88
Talked about on Bluesky, YouTube, the web and Hacker News (88 times).
On Bluesky · 47
- Oct 19, 2026🎉 Celebrating! 🎉 (500+ new stars) 📦 ruvnet / ruflo ⭐ 76,913 (+564) 🗒 TypeScript 🌊 The original agent harness. Deploy intelligent… — @github-trending.bsky.social4 likes and reposts · 1 reply
- Jul 2, 2026🚀 Skyrocketing! 🚀 (200+ new stars) 📦 ruvnet / ruflo ⭐ 62,550 (+233) 🗒 TypeScript 🌊 The leading agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social3 likes and reposts · 1 reply
- May 10, 2026Here's a GitHub repo I found impressive: Ruflo makes it easy to orchestrate 100+ AI agents with security, coordination, and seamless Claude… — @alexiskirke.bsky.social3 likes and reposts
- May 4, 2026今日のGitHubトレンド ruvnet/ruflo RufloはClaude Code向けのマルチエージェントAIオーケストレーションツールです。 100以上の専門AIエージェントを連携させ、異なるマシンやチーム間での協調的な動作を実現します。… — @dailygithubtrends.bsky.social3 likes and reposts
- May 2, 2026💎 Hidden Gem! 💎 (1000+ new stars) 📦 ruvnet / ruflo ⭐ 35,779 (+1,258) 🗒 TypeScript 🌊 The leading agent orchestration platform for… — @github-trending.bsky.social3 likes and reposts · 1 reply
42 more on Bluesky
- Mar 2, 2026Enterprise-grade AI agent orchestration platform that turns Claude into coordinated multi-agent swarms with 60+ specialized agents,… — @arifsolmaz.bsky.social3 likes and reposts
- Oct 3, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 73,707 (+101) 🗒 TypeScript 🌊 The original agent harness. Deploy intelligent… — @github-trending-js.bsky.social2 likes and reposts
- Jul 27, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 66,205 (+174) 🗒 TypeScript 🌊 The leading agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social2 likes and reposts
- Jul 19, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 65,114 (+160) 🗒 TypeScript 🌊 The leading agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social2 likes and reposts
- Jul 12, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 64,108 (+156) 🗒 TypeScript 🌊 The leading agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social2 likes and reposts
- Jul 1, 2026As much as I pan the idea of software dark factories, I can't help but be curious. Today's exploration is building a CMS on top of our… — @andrewhao.com2 likes and reposts · 1 reply
- Jun 21, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 60,647 (+182) 🗒 TypeScript 🌊 The leading agent meta-harness for Claude. Deploy… — @github-trending-js.bsky.social2 likes and reposts
- May 6, 2026💎 Hidden Gem! 💎 (1000+ new stars) 📦 ruvnet / ruflo ⭐ 44,684 (+2,432) 🗒 TypeScript 🌊 The leading agent orchestration platform for… — @github-trending-js.bsky.social2 likes and reposts · 1 reply
- May 4, 2026ruvnet/ruflo 🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous… — @wasm.activitypub.awakari.com.ap.brid.gy2 likes and reposts
- Apr 25, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 33,217 (+160) 🗒 TypeScript 🌊 The leading agent orchestration platform for Claude.… — @github-trending-js.bsky.social2 likes and reposts
- Mar 29, 2026Ruflo (github.com/ruvnet/ruflo) reduces token usage by atleast 40% without impacting quality Will try to share a detailed report… — @adityamitra.bsky.socialsays it tested it2 likes and reposts
- Mar 24, 2026💎 Hidden Gem! 💎 (1000+ new stars) 📦 ruvnet / ruflo ⭐ 24,437 (+1,397) 🗒 TypeScript 🌊 The leading agent orchestration platform for… — @github-trending-js.bsky.social2 likes and reposts · 1 reply
- Mar 5, 2026Ruflo : plateforme d'orchestration pour déployer des essaims d'agents Claude autonomes, avec workflows distribués, RAG et intégration… — @camilleroux.com2 likes and reposts · 1 reply
- Mar 2, 2026今日のGitHubトレンド ruvnet/ruflo Ruflo v3は、企業向けのAIオーケストレーションプラットフォームです。 大規模言語モデル(LLM)を活用し、AIエージェントの構築・運用を支援します。 Claude Code… — @dailygithubtrends.bsky.social2 likes and reposts
- Mar 1, 2026ClaudeなどのLLMを扱うためのマルチエージェント調整プラットフォームらしい 自律的なワークフロー調整やAIチーム構築に期待 yug1224 starred ruvnet/ruflo https://github.com/ruvnet/ruflo — @yug1224.com2 likes and reposts
- Feb 28, 2026今日のGitHubトレンド ruvnet/ruflo Ruflo v3は、企業向けのAIオーケストレーションプラットフォームです。 大規模言語モデル(LLM)を活用し、AIエージェントの構築・運用を支援します。 Claude Code… — @dailygithubtrends.bsky.social2 likes and reposts
- Feb 28, 2026🎉 Celebrating! 🎉 (500+ new stars) 📦 ruvnet / ruflo ⭐ 15,591 (+531) 🗒 TypeScript 🌊 The leading agent orchestration platform for Claude.… — @github-trending.bsky.social2 likes and reposts · 1 reply
- Oct 20, 2026今日のGitHubトレンド ruvnet/ruflo Claude CodeやCodexなどのAIエージェント向けに、コアツールや管理コンソール、ランタイムモッドを提供するメタハーネスです。… — @dailygithubtrends.bsky.social1 likes and repost
- Oct 19, 2026🎉 Celebrating! 🎉 (500+ new stars) 📦 ruvnet / ruflo ⭐ 76,328 (+502) 🗒 TypeScript 🌊 The original agent harness. Deploy intelligent… — @github-trending-js.bsky.social1 likes and repost · 1 reply
- Oct 6, 2026📦 ruvnet / ruflo ⭐ 73,984 (+87) 🗒 TypeScript 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous… — @github-trending-js.bsky.social1 likes and repost
- Aug 23, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 68,977 (+134) 🗒 TypeScript 🌊 The original agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social1 likes and repost
- Aug 22, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 68,621 (+140) 🗒 TypeScript 🌊 The original agent meta-harness. Deploy intelligent… — @github-trending.bsky.social1 likes and repost
- Aug 19, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 68,298 (+143) 🗒 TypeScript 🌊 The original agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social1 likes and repost
- Aug 10, 2026🔥 Hot Repo! 🔥 (100+ new stars) 📦 ruvnet / ruflo ⭐ 67,541 (+114) 🗒 TypeScript 🌊 The original agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social1 likes and repost
- Jun 17, 2026🚀 Skyrocketing! 🚀 (200+ new stars) 📦 ruvnet / ruflo ⭐ 59,913 (+200) 🗒 TypeScript 🌊 The leading agent meta-harness for Claude. Deploy… — @github-trending-js.bsky.social1 likes and repost
- Jun 1, 2026🚀 Skyrocketing! 🚀 (200+ new stars) 📦 ruvnet / ruflo ⭐ 57,130 (+354) 🗒 TypeScript 🌊 The leading agent meta-harness for Claude. Deploy… — @github-trending-js.bsky.social1 likes and repost · 1 reply
- May 5, 2026ruvnet/ruflo 🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous… — @wasm.activitypub.awakari.com.ap.brid.gy1 likes and repost
- May 4, 2026New GitHub trending project: ruflo - agent orchestration platform for Claude. 40k+ stars! https://github.com/ruvnet/ruflo #AI #OpenSource… — @samwise-goose.bsky.social1 likes and repost
- May 3, 2026ruvnet/ruflo 🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous… — @wasm.activitypub.awakari.com.ap.brid.gy1 likes and repost
- May 2, 2026💎 Hidden Gem! 💎 (1000+ new stars) 📦 ruvnet / ruflo ⭐ 35,779 (+1,258) 🗒 TypeScript 🌊 The leading agent orchestration platform for… — @github-trending-js.bsky.social1 likes and repost · 1 reply
- May 2, 2026今日のGitHubトレンド ruvnet/ruflo RufloはClaude CodeのためのマルチエージェントAIオーケストレーションツールです。… — @dailygithubtrends.bsky.social1 likes and repost
- Mar 25, 2026今日のGitHubトレンド ruvnet/ruflo RuFlo v3.5は、企業向けのAIオーケストレーションプラットフォームです。 大規模言語モデル(LLM)を活用し、AIエージェントの構築・運用を支援します。 Claude Code… — @dailygithubtrends.bsky.social1 likes and repost
- Mar 24, 2026💎 Hidden Gem! 💎 (1000+ new stars) 📦 ruvnet / ruflo ⭐ 24,437 (+1,397) 🗒 TypeScript 🌊 The leading agent orchestration platform for… — @github-trending.bsky.social1 likes and repost · 1 reply
- Mar 4, 2026🎉 Celebrating! 🎉 (500+ new stars) 📦 ruvnet / ruflo ⭐ 18,540 (+666) 🗒 TypeScript 🌊 The leading agent orchestration platform for Claude.… — @github-trending-js.bsky.social1 likes and repost · 1 reply
- Mar 2, 2026github.com/ruvnet/ruflo GitHub - ruvnet/ruflo: 🌊 The leading agent orchestration platform for Claude. Deploy intelligent... — @technews4869.bsky.social1 likes and repost
- Feb 28, 2026🎉 Celebrating! 🎉 (500+ new stars) 📦 ruvnet / ruflo ⭐ 15,591 (+531) 🗒 TypeScript 🌊 The leading agent orchestration platform for Claude.… — @github-trending-js.bsky.social1 likes and repost · 1 reply
- Sep 11, 2026Coordinate multiple agents, tools, memory and workflows. https://github.com/ruvnet/ruflo 7. OpenCode Agents Ready-to-use specialized agents… — @garrytan-mir-rt.selfhosted.social0 likes and reposts · 1 reply
- Sep 10, 2026This builds a minimal agent harness from scratch. https://github.com/shareAI-lab/learn-claude-code 6. Ruflo A multi-agent orchestration… — @garrytan-mir-rt.selfhosted.social0 likes and reposts · 1 reply
- Sep 6, 2026🚀 Skyrocketing! 🚀 (200+ new stars) 📦 ruvnet / ruflo ⭐ 70,842 (+276) 🗒 TypeScript 🌊 The original agent meta-harness. Deploy intelligent… — @github-trending-js.bsky.social0 likes and reposts · 1 reply
- Jul 23, 2026一次情報を見ると、rufloはちゃんと本格的ですぅ。フル導入では98エージェント、MCP、フック、常駐プロセスまで入るオーケストレーターです。… — @lutie-echosphere.bsky.social0 likes and reposts · 1 reply
- Jul 18, 2026公式GitHubを確認。Rufloは100超の専門エージェント、ベクトルメモリ、学習用パターンを実装対象にしている。単なるプロンプト集ではない。 ただ、公式Quick Startの最初のswarm例は最大8… — @nemu-echosphere.bsky.social0 likes and reposts · 1 reply
- May 6, 2026💎 Hidden Gem! 💎 (1000+ new stars) 📦 ruvnet / ruflo ⭐ 44,684 (+2,432) 🗒 TypeScript 🌊 The leading agent orchestration platform for… — @github-trending.bsky.social0 likes and reposts · 1 reply
On YouTube · 23
- Mar 31, 2026Claude Code with RuFlo v3.5: Enterprise AI Orchestration Platform — Kaya Rezende35k views · 31 comments
- May 3, 2026ruflo: Turn Claude Code into a Swarm of 100 AI Agents — Hungry Labs14k views · 4 comments
- Aug 24, 2026Ruflo GitHub Setup Guide: Register Claude Flow MCP and Verify Persistent Memory Recall — Alex Hitt4.5k views
- Jun 15, 2026Ruflo Explained: Multi-Agent AI Orchestration for Claude Code & Beyond — @BytesAndBricks1.8k views
- Jun 6, 2026Ruflo - Multi-Agent AI Harness for Claude Code & Codex — Kuro1.5k views
18 more on YouTube
- Oct 17, 2026RuFlo: Building Reliable Agent Swarms — CLI Stack1.3k views
- Oct 9, 2026ruflo: Conductor #Shorts — Cognitum One Team810 views · 3 comments
- May 5, 2026ruflo - GitHub Trending Today — GitHub Trending Digest778 views
- Oct 15, 2026Claude Code와 Codex를 위한 multi-agent harness, ruflo — 굿리포546 views
- Jun 3, 2026🚀 Ruflo Explained | The AI Framework That Turns One AI Into an Entire Company 🤖👑 — QA_AI_WIZARDS535 views
- Oct 17, 2026ruflo: Coordinate AI agents instantly — Daily Finds Dev | Repos, Tools, Sites364 views
- Sep 11, 2026Ruflo: build conversational AI with autonomous swarm workflows — Next Horizon354 views · 1 comment
- Oct 30, 2026Claude Code + Ruflo setup: worth it, or what's the catch? — OverClocked323 views · 1 comment
- Oct 26, 2026Ruflo - A team of coding agents with roles and a budget (79k stars) — Evolution with AI276 views
- Oct 9, 2026ruflo: Model + Harness #Shorts — Cognitum One Team63 views
- Sep 6, 2026ruvnet/ruflo — It is the harness, not the model: sandboxes, loops, and memory that recalls … #Shorts — Fresh Commits54 views
- Oct 26, 2026🌊 Ruflo turns Claude Code into an actual agent team #codeprep #programming — GitGemVault49 views
- Oct 9, 2026ruflo: One Command #Shorts — Cognitum One Team49 views
- Oct 30, 2026Coding Agents Get a Cockpit (Ruflo) — Github God Eng37 views
- Nov 4, 2026ruflo: The Hottest TypeScript Repo on GitHub Right Now #Shorts — Repo Radar30 views
- Oct 26, 2026Day7 - AN - Ruflo define a mission and track agents (EN) — CPPAI23 views
- Oct 18, 2026ruflo — Trending on GitHub | Repo & Resources — Repo & Resources16 views
- Nov 4, 2026ruflo: The Hottest TypeScript Repo on GitHub Right Now — Repo Radar5 views
On the web · 16
- Oct 6, 2026Ruflo + Codex: experimenting with agent orchestration, MCP and multi-agent software delivery. — linkedin.com
- Oct 5, 2026ruflo 입문 가이드 — Claude Code 멀티 에이전트 오케스트레이션 시작 — dev-post.com
- Oct 2, 2026Ruflo 조사: Claude Code 위에 올리는 멀티 에이전트 하네스, 무엇이 진짜이고 무엇이 아닌가 · LaMelD — lameld.github.io
- Sep 7, 2026Ruflo (hơn 70 nghìn sao) - bộ khung vận hành cho AI agent, lắp thêm đội hình và trí nhớ cho Claude Code và Codex — phongminhho.substack.com
- Sep 2, 2026Why `ruvnet/ruflo` Is Gaining Attention for Multi-Agent Workflows — dev.to
11 more on the web
- Jul 5, 2026A Field Guide to Multi-Agent Orchestration in Late 2025: ruflo, KARIMO, llm-council — dev.to
- May 28, 2026Treating an agent swarm as the unit of work — ruvnet/ruflo – EZPZ AI — ezpzai.com
- May 24, 2026With the agent-orchestrator shelf this full, what does one more add — ruvnet/ruflo – EZPZ AI — ezpzai.com
- May 14, 2026The orchestrator-on-top-of-Claude-Code category is filling in fast — ruvnet/ruflo – EZPZ AI — ezpzai.com
- May 12, 2026Ruflo: How to Turn Claude Code Into a Multi-Agent Swarm (Setup Guide) | by Karthikmulugu | May, 2026 — medium.com
- May 7, 2026Ruflo (Claude Flow): Multi-Agent Deep Dive | Jared Smith — sublimecoding.com
- May 6, 2026How Ruflo Turns Claude Code Into a Multi-Agent Platform With Memory, Swarms, and Federation — alphasignalai.substack.com
- May 5, 2026How to use ADRs in RuFlo 🌊 ADRs are quietly becoming one of the most important primitives in agentic engineering. — linkedin.com
- May 5, 2026Stop Treating Claude Code Like a Single Assistant — youraiweeklyroundup.substack.com
- Apr 5, 2026Been using Ruflo (formerly Claude Flow) for the past couple weeks and it's changed how I work with Claude Code in a pretty fundamental way. | Devesh Jaluka — linkedin.com
- Mar 23, 2026Ruflo: Multi-Agent Orchestration for Claude Code | Viktor Avelino — viktoravelino.com
On Hacker News · 2
- Jul 25, 2026Ruflo: An agent meta-harness for Claude Code and Codex3 points
- Apr 29, 2026Is any one using ruflo?1 point · 1 comment
Other versions27 projects use a version of this.
Word for word · 23
- ruvnet/wifi-densepose★ 103k100% same
- ruvnet/RuView★ 103k100% same
- ruvnet/claude-flow★ 80k100% same
- ruvnet/ruvector★ 4.7k100% same
- ruvnet/RuVector★ 4.7k100% same
- proffesor-for-testing/agentic-qe★ 524100% same
- ruvnet/ruv-FANN★ 388100% same
- spencermarx/open-code-review★ 382100% same
- tokendad/NesVentory★ 93100% same
- shyftlabs/continuum★ 84100% same
13 more not listed
Edited · 4
- ruvnet/agentic-flow★ 838100% same
- Zekiog/ruflo★ 2100% same
- fidgetcoding/fidgetflo★ 199% same
- jpoindexter/theft-kit★ 1100% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository177 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/commands/monitoring/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- v3/CLAUDE.mdCLAUDE.md
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The file
Files
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% reductionMCP 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")Does it work?
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