Tech Stack
Architecture
FastMCP server (stdio transport) -> Tool definitions with typed parameters -> Resource endpoints for context -> Prompt templates for common operations. Each server = one domain boundary.MCP (Model Context Protocol) is what turns AI chatbots into AI agents that can actually do things. I've built 10+ MCP servers — here's the pattern.
The Architecture: Every MCP server follows the same structure: FastMCP for the server framework, stdio transport for local agents (or HTTP for remote). Tools are functions with typed parameters and clear descriptions. Resources provide context data. Prompts template common operations.
One Domain, One Server: The Zoho CRM MCP server only handles CRM operations. The Facebook Ads MCP server only handles ad management. This separation means each server is small, testable, and reusable. When I need CRM access in a new project, I just add the server to the MCP config — no code changes.
The Euron Setup: 8 MCP servers for the AI education platform: course management, student support, analytics, content generation, assignment grading, forum moderation, enrollment, and billing. Each server connects to PostgreSQL and exposes 5-15 tools.
Building Fast: With FastMCP, a basic server takes 30 minutes. Define your tools as Python functions with type hints, add docstrings for the AI to understand when to use them, and you're done. The framework handles serialization, error handling, and transport.
The Business Model: Custom MCP server development starts at $800. Most clients need 2-3 servers to connect their existing tools (CRM, database, internal APIs) to AI agents. It's a clean, repeatable service with high margins.
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