Custom MCP servers that connect Claude, GPT, and other AI models directly to your tools, databases, and APIs. No middleware. No prompt-stuffing. Real tool use.
Model Context Protocol is how AI models use tools. Not through hacky prompt injections or screenshot scraping. Through structured, typed, secure connections that let the model call your API the same way a developer would.
An MCP server wraps your business logic, your database, your CRM, your internal tools, and exposes them as callable functions. The AI model sees what's available, picks the right tool, passes the right parameters, and gets structured results back. No hallucinated API calls. No guesswork.
Dr. Zac Smith builds MCP systems at Gauntlet AI, where engineers train for $200k+/yr roles at companies like Zapier and Carvana. His PhD is in Cybersecurity Engineering. When your MCP server touches production data and customer records, that combination of AI expertise and security discipline is the difference between a demo and a deployed system.
# What We Build
Custom MCP Servers
Bespoke servers that expose your specific tools and data to AI models. CRM lookups, database queries, internal APIs, file operations, workflow triggers. Whatever your business runs on, wrapped in a clean, typed interface.
GoHighLevel + N8N MCP
Connect AI directly to your GHL CRM and N8N automation workflows. Contacts, pipelines, conversations, and workflow triggers accessible as native AI tools. No Zapier tax. No middleware latency.
Database & API Connectors
MCP servers for Supabase, PostgreSQL, MongoDB, REST APIs, and GraphQL endpoints. Scoped read/write permissions, query validation, and rate limiting baked in. Your data stays secure while AI gets structured access.
Multi-Server Orchestration
Complex workflows need multiple MCP servers coordinating. Your CRM server talks to your analytics server, which feeds your reporting server. We architect the full graph, not just individual endpoints.
Security-First Architecture
Every MCP server we build follows principle of least privilege. Scoped tokens, encrypted transport, input validation, audit logging. Built by someone whose doctorate is literally in cybersecurity engineering.
Migration & Integration
Already using AI tools with clunky integrations? We replace fragile prompt-chains and screenshot-based automation with proper MCP connections. Same AI, dramatically better reliability.
# Why MCP Changes Everything
Before MCP, connecting AI to your tools meant prompt engineering hacks. You'd paste API docs into the system prompt and hope the model figured it out. Sometimes it worked. Often it hallucinated endpoints, mangled parameters, or silently failed.
MCP replaces hope with protocol. The model knows exactly what tools exist, what parameters they accept, and what they return. It's the difference between handing someone a phone book and giving them speed dial.
Companies that adopt MCP early get AI that actually works with their systems. Companies that wait get left with increasingly brittle prompt-chains while their competitors build real AI infrastructure.