Session Overview
In this session, Ahmed Ibrahim and Shaghayegh Moradirad break down the hidden costs and latency bottlenecks of building AI agents with Model Context Protocol (MCP). Learn key engineering takeaways from building agent runtimes, including context window bloat, tool composability, code mode, and prompt caching economics.
What You'll Learn
- What MCP is and how it extends agent systems
- The real cost of front-loading schemas and tool definitions
- Why naming clarity prevents agent hallucinations and failure modes
- Trimming tool outputs to avoid context flooding
- Tool composability and using runtime scripts (Code Mode) vs sequential round-trips
- The hidden cost dynamics of cached tokens over multi-turn agent runs
- Design principles for building fast, cost-effective agent environments
Chapters
- 00:00 — Introduction & what is MCP?
- 01:21 — Pitfall 1: Loading too many tools upfront
- 03:03 — Pitfall 2: Ambiguous tool naming & scoping
- 04:20 — Pitfall 3: Massive tool outputs & context bloating
- 05:46 — Pitfall 4: Tool composability & Code Mode
- 08:13 — Pitfall 5: The myth of cheap cached tokens
- 09:35 — Summary: Core rules for designing efficient MCP servers
- 12:50 — Q&A wrap-up
