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AI Engineering · Agents In Production

MCP in Production: What the Protocol Buys and Costs

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The rest of this lesson

  1. Host, Client, Server: Who Holds What
  2. stdio and HTTP: Two Wires, Two Trust Models
  3. How a Client Discovers and Calls a Tool
  4. Every Attached Server Pays Rent in the Context Window
  5. Put a Number on the Rent
  6. Prompt Caching Lowers the Bill, Not the Window
  7. Price One Agent Task by Hand
  8. More Tools, Worse Choices
  9. The Extra Hop, and the Versions and Auth You Now Own
  10. When MCP Pays, and When a Function Call Wins
  11. Four Mistakes I See With MCP Setups

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    Eight Servers Attached, Ten Thousand Tokens Gone Before the User Types

    Attach eight servers to an agent and roughly ten thousand tokens of tool descriptions ride in the context window on every request, before the user has said a word. In a loop that runs ten model calls to finish a task, you pay that ten times. Nobody put that line in the budget.

    This is the part the Model Context Protocol pitch skips. The pitch is real: MCP standardizes how models discover and call tools, and it collapses a pile of bespoke integrations into a clean protocol. What the pitch leaves out is that every server you attach has a running cost that shows up on every request, and that cost is easy to rack up because attaching a server is one line of config that looks free.

    The contract lesson earlier in this chapter covered how a single call is validated and why the model breaks it. That lesson stands whether or not you use MCP. This one is about the layer above: what MCP actually is, what standardizing tool access buys you, and the bill that arrives with it. By the end you will be able to price an MCP setup in tokens and latency, and decide when it earns its keep versus when a plain function call is the better engineering.

    What MCP Actually Standardizes

    Strip away the branding and is a client-server protocol for one job: letting a model discover what tools exist and call them, in a format that any compatible client and any compatible server agree on.

    The value is an integration-effort argument. Picture N agent surfaces (a coding agent, an internal ops bot, a support assistant) and M capabilities (GitHub, a Postgres database, a payments API). Without a shared protocol, each surface wires up each capability in that provider's own way, which is N times M pieces of glue. Add a capability and you re-plumb it into every surface. Change one tool's arguments and you edit it in N places.

    MCP integration math: without a shared protocol three agent surfaces each wire up three capabilities for nine bespoke adapters, and with MCP the same three surfaces and three capability servers connect through one protocol bus for six interfaces, collapsing the N times M matrix to N plus M

    MCP makes each capability a server, described once, and each surface a host that speaks the protocol once. The matrix collapses from N times M pairwise adapters to N plus M interfaces. A new capability is one new server that every existing host can use, with no per-surface adapter.

    That collapse is genuine, and on a large matrix it is a real saving. Hold onto one thing though: the reduction is in the work of wiring things together, not in what each server costs at runtime. Every server a host attaches still occupies context and adds a hop on every request, which is the bill the rest of this lesson makes you look at.