Question 1

What is MCP and why does my product need a server now?

Accepted Answer

MCP (Model Context Protocol) is an open standard that lets AI assistants like Claude and ChatGPT call your product directly: read data, run actions, answer questions. An MCP server is the piece you ship to make that possible. Customers are already asking vendors whether their products work with AI assistants, and assistants are becoming a real interface to software. A server is how your product shows up in that conversation instead of being paraphrased from a help page.

Question 2

How does an MCP server relate to my existing API?

Accepted Answer

It sits on top of it. Your API stays the source of truth. The MCP server defines a tool surface: a curated set of operations with schemas, descriptions, and guardrails written for a model to use correctly. Good tool design is editorial work, not a mechanical wrapper. Exposing every endpoint one to one usually produces an agent that fumbles.

Question 3

How do you handle auth and multi-tenant security?

Accepted Answer

Remote MCP servers authenticate users with OAuth. Every tool call runs in the context of the authenticated user and their tenant, with the same permission checks your application already enforces. The model never gets a master key. I design tenancy and permission enforcement first, because retrofitting it later is the most expensive mistake in this space.

Question 4

What about prompt injection and tool misuse?

Accepted Answer

It is a real risk and the design accounts for it. Destructive operations are separated from reads, gated behind confirmation, or excluded entirely. Inputs are validated against strict schemas, rate limits apply per user, and the eval suite includes adversarial cases. The risk review in the assessment covers this for your specific product.

Question 5

What if the protocol or the model vendors change?

Accepted Answer

MCP is an open standard with adoption across the major model vendors, so it is not a bet on one company. The server I build is a thin, well-documented layer over your API: if the protocol moves, you update that layer, not your product. You own the code, and the 30-day stabilization period covers anything that shifts right after launch.

Question 6

Who owns the code?

Accepted Answer

You do, fully. The server is deployed to your infrastructure, the repository is yours, and it ships with documentation, runbooks, and an eval suite your team can run. There is no dependency on me after handoff unless you want one.

Question 7

What does it cost and how is payment structured?

Accepted Answer

The agent-readiness assessment is a fixed $3,500, and it credits toward a build if you proceed. An MCP server build starts at $15,000 and AI feature work starts at $25,000, with a fixed price set after scoping. Payment is 50% at project start, 30% at the midpoint demo, and 20% at production launch.

Question 8

Why a solo consultancy instead of an agency?

Accepted Answer

Because the person who scopes your project is the person who designs it, builds it, and answers for it in production. No handoffs, no junior subcontractors, no margin stacked on someone else’s work. The tradeoff is honest: I take a limited number of projects, and each one is scoped tightly so it ships.

Question 9

What happens after launch?

Accepted Answer

Every build includes a 30-day stabilization period: monitoring, fixes, and adjustments while real usage arrives. After that you can run it yourself with the docs and runbooks, or keep me involved through a fractional arrangement. Most of the post-launch work is already done by then, because evals and monitoring are part of the build, not an afterthought.

Make your SaaS agent-ready.

AI assistants are becoming a primary interface to software.

Three ways to engage.

MCP server sprint

AI feature implementation

Fractional AI architect

The architect who scopes the work builds it.

Scoping call

Discovery

Iterative build

Stabilization and handoff

What founders and CTOs ask before booking.

Your customers are already asking their assistants about your product.