MCP Server Development: Connect Your Tools to AI Agents

What an MCP server actually is

An MCP server is a small program that advertises three kinds of capability to an AI client: tools (functions the model can call), resources (data it can read), and prompts (reusable templates). The client handles the model; your server handles the connection to reality.

The value is that you write the integration once. Without MCP, every assistant that needs to query your database or file a ticket in your system needs its own bespoke connector.

Where teams get it wrong

Exposing the API surface instead of the task. The instinct is to wrap every endpoint as a tool. It produces a server with sixty tools that the model chooses badly between. Tools should map to tasks a user wants done — find_overdue_invoices beats GET /invoices plus list_filters plus get_customer.

Vague tool descriptions. The description is the prompt. "Searches records" tells the model nothing about when to reach for it. Describe what it returns, what arguments mean, and when not to use it.

No pagination or truncation. A tool that returns 40,000 rows blows the context window and the call fails. Return a bounded page plus a cursor, and say in the description how to get more.

Unbounded permissions. The server runs with whatever credentials you gave it, and the model decides when to use them. A tool that can delete needs a confirmation path or should not exist.

Design decisions that matter

Transport. stdio for local servers the client launches itself; HTTP with Server-Sent Events for remote servers serving multiple users. Remote means you now own authentication, tenancy, and rate limiting.

Authentication. For remote servers, OAuth so each user's calls run under their own identity. A single shared service account means every user sees everything that account can see — the most common security mistake we're asked to fix.

Error messages are prompts too. When a tool fails, the model reads the error and decides what to do. "Error 403" produces a retry loop. "You do not have access to this workspace; ask the user which workspace to use" produces the right next action.

Idempotency. Models retry. Any tool that writes needs an idempotency key so a retry doesn't create a duplicate record.

What we build

A scoped MCP server against your systems: tool design driven by the tasks users actually ask for, OAuth where the server is remote, structured errors, pagination, and an evaluation set that checks the model picks the right tool for realistic requests. Typically two to three weeks.

We also do the unglamorous part — deciding which operations should not be exposed to a model at all, and putting a human approval gate on the ones that stay.