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Five-day tracks

5 Days of MCP for Production AI

What the Model Context Protocol standardises, where servers run, and when MCP earns its overhead.
6 min in total
  1. 01

    Part 1 · Explainer · 1 min read

    What the MCP protocol actually standardises

    It settles how capabilities are described and discovered. Every decision about whether to trust them is still yours.

    On the map: Tools
  2. 02

    Part 2 · Explainer · 2 min read

    Where your MCP server runs is a production decision

    Transport looks like a technical detail during the demo. It is really a choice about ownership, reachability and trust.

    On the map: Tools
  3. 03

    Part 3 · Explainer · 1 min read

    Tools, resources and prompts are not interchangeable

    Choosing the wrong primitive hands the model authority a person was supposed to hold.

    On the map: Tools
  4. 04

    Part 4 · Explainer · 1 min read

    A clean connector does not make a reliable agent

    Connector correctness and agent behaviour are separate problems. Most teams only test the first one.

    On the map: Tools
  5. 05

    Part 5 · Comparison · 1 min read

    When MCP earns its overhead, and when a direct API is better

    One question settles most of these arguments: will more than one AI application need this capability?

    On the map: Tools, Enterprise APIs