AI Agent Platform with MCP Servers | Multi-Business AI Agent Platform for Founder

Built a multi-agent AI platform connecting 40+ systems across six businesses, delivering 21 automated workflows, custom MCP infrastructure, and approximately $35K in annual savings.

Overview

A production multi-agent AI platform I designed and built for a founder managing six businesses. It connects 40+ business systems through 21 automated workflows and three custom Model Context Protocol (MCP) servers, providing a centralized AI-powered operational command center.

The Problem

Business operations were fragmented across disconnected applications, inboxes, databases, and documents. Manual financial workflows, unreliable knowledge retrieval, and limited operational visibility created inefficiencies across the businesses.

The Solution

• Built 21 automated workflows with specialized, tool-calling agents connecting 40+ business systems, including QuickBooks, CRM platforms, and Google Workspace.
• Developed three custom MCP servers with structured agent-to-system communication, three autonomy tiers, per-business credential isolation, OAuth integrations, and human approval gates.
• Developed agent execution infrastructure with reusable skills, context memories, multi-agent configurations, and context optimization.
• Rebuilt the production retrieval pipeline, improving retrieval coverage from 0.3% to over 90% with source citations.
• Implemented durable agent execution, checkpointing, retries, monitoring, and offline evaluation. Identified and fixed five silent failures.
• Reduced a $1,000+/week LLM cost overrun through context pruning and intelligent Claude model routing.

Business Impact & Results

• ~$35K in total annual savings.
• 15 hours/week of manual work eliminated through invoice and payment exception automation.
• ~60% faster incident resolution.
• 0.3% → 90%+ retrieval coverage.
• $1,000+/week in LLM cost overruns eliminated.
• 5 production failures identified and fixed.

My Role

Forward Deployed AI Engineer & Technical Lead

Owned end-to-end delivery, from client discovery and AI architecture to agent development, backend engineering, MCP integrations, testing, deployment, and production optimization. Built using Claude Code and specification-driven, AI-assisted software development.

Technology Stack & Engineering Expertise

• Agentic AI: Multi-Agent Systems, LangGraph, Claude, OpenAI, Agent Orchestration, Tool Calling, Model Routing.
• Context & Retrieval: Context Engineering, Agent Skills, Context Memories, RAG, Semantic Search, pgvector, Pinecone, NuMind.
• MCP & Integrations: Custom MCP Servers, Multi-Tenant Architecture, OAuth, QuickBooks, HubSpot, Salesforce, Google Workspace, n8n.
• Backend & Cloud: Python, FastAPI, PostgreSQL, AWS, Event-Driven Architecture, Durable Execution.
• Production AI: LangSmith, LLM Observability, Evaluation, Regression Testing, Agent Monitoring, Cost Optimization, Claude Code.