Model Context Protocol (MCP): Tool Ergonomics for Production Agents
Anthropic's open Model Context Protocol (MCP) establishes a universal standard for AI tool integrations. Here is how we design high-efficiency, token-conserving MCP servers for real-world enterprise infrastructure.
1. Why Standardized Agent Tooling Matters
Before MCP, every AI agent framework invented its own proprietary function calling schemas. Swapping an agent engine required rewriting hundreds of custom tool definitions.
MCP standardizes tools, resources, and prompt templates over JSON-RPC. Inside CraftCode, we use MCP to connect agents directly to local PostgreSQL databases, git trees, terminal runners, and remote staging servers.
2. Three Rules for Production MCP Servers
- 01. Lazy Load Tool Schemas: Never register 50+ monolithic tool schemas eagerly in the system prompt. Use metadata-first discovery to keep token overhead near zero until a tool is actually required.
- 02. Structured JSON Error Responses: When a tool fails, return structured diagnostic fields (`errorCode`, `suggestion`, `remedy`) rather than opaque string exceptions.
- 03. Deterministic Sandboxing: Wrap destructive operations in dry-run simulation gates before executing live mutations against production databases.
ABOUT THE AUTHOR
Build MCP Agent SystemsSakshyam Pokhrel
Founder of CraftResearch Tech. Building autonomous agents and MCP tooling.
pokhrel.tech ↗