Alejandro Ponce de León

Software Engineer

Alejandro is a software engineer specializing in AI agent infrastructure and Model Context Protocol (MCP) tooling, helping enterprises deploy secure, scalable AI solutions. He architected the MCP Optimizer, a hybrid semantic and keyword search system that achieves 94% accuracy in tool selection across nearly 3,000 tools, dramatically outperforming existing approaches. He also created mcp-tef, a testing and evaluation framework that helps developers validate MCP tool quality before production. Prior to Stacklok, Alejandro held technical roles at Nokia and Cisco.

All Articles by Alejandro Ponce de León

March 11, 2026

Cut token waste across your entire team with the MCP Optimizer

Stacklok’s MCP Optimizer scales from laptop to cluster: one shared deployment slashes token costs for every team member and AI agent.

January 30, 2026

Build your first enterprise MCP server with GitHub Copilot

Ever wondered how to bridge the gap between your company’s private knowledge and AI assistants? You’re about to vibecode your way there.

December 10, 2025

Stacklok’s MCP Optimizer vs Anthropic’s Tool Search Tool: A head-to-head comparison

Both solutions tackle the critical problem of token bloat from excessive tool definitions. See how they stack up in a head-to-head test of tool selection accuracy.

More Authors

Chris Burns

Software Engineer
Dan Barr

Dan Barr

Senior Technical Marketing Engineer

Jakub Hrozek

Staff Software Engineer