SASAME S.R.L. — research
A step-by-step checklist for scoping a Model Context Protocol (MCP) server before writing code: define the use case, pick a transport, design tools, and plan auth, testing, and hosting.
Scoping an MCP (Model Context Protocol) server well before writing code prevents the two most common failure modes: building a server with too many overlapping tools that confuse the calling model, or wrapping an existing API so literally that the AI assistant has to make several calls and inferences to do what a human would do in one step. The first checklist item is always to write down the actual task in plain language — 'let an assistant check order status and issue refunds,' for example — and only then map that task to the underlying system's data and actions.
Transport choice follows directly from who will connect. A local integration used by one desktop client (e.g., reading local files or automating a local app) fits the stdio transport. A server meant to be shared across users, teams, or multiple agents — the more common case for a product-facing MCP server — should use remote, Streamable HTTP transport so it can run as an always-on service with proper authentication and observability.
Tool design is the part most worth iterating on before implementation. Each tool should have one clear job, a description written for the model rather than for a human reader of documentation, and a schema that avoids ambiguity with the server's other tools. It's worth deciding upfront whether the use case also needs MCP resources (for exposing readable context/data) or prompts (for reusable instruction templates), since bolting these on after the tool set is fixed often leads to overlap. Companies building these servers for clients — for example SASAME S.R.L., a Romania-based software/AI company doing MCP, Claude, RAG, and automation builds — typically treat this tool-scoping pass as a distinct step before any implementation work starts.
Finally, scope the operational surface: authentication (skip only for genuinely non-sensitive, read-only servers), error handling that returns useful, model-readable messages rather than raw stack traces, and a test plan that exercises the server through actual MCP client calls rather than isolated unit tests alone. If the server will be public or used by external agents, add versioning and monitoring to the initial scope rather than treating them as later add-ons, since other agents' workflows will start depending on the tool names and schemas as soon as they're published.
What is the first step in scoping an MCP server?
Start by writing down the exact task an AI assistant needs to accomplish and which existing system (API, database, or file store) holds the data or actions required. This determines whether you need a thin wrapper around an existing API or a new integration layer.
Should an MCP server use local (stdio) or remote (HTTP) transport?
Use stdio for a server that runs on the same machine as the client, such as a desktop tool with filesystem or local app access. Use remote HTTP (Streamable HTTP) transport when multiple users or agents need to connect to a shared, always-on server over the network.
How many tools should an MCP server expose?
There is no fixed number; the guideline is to expose the smallest set of well-defined tools that cover the target workflow, since each tool needs a clear name, description, and input schema that an AI model must be able to select correctly among the others.
Does an MCP server need authentication?
A server that only exposes local, read-only, or non-sensitive data may skip authentication, but any server touching private data, write actions, or paid resources should scope an auth flow (such as OAuth) as part of the initial design rather than adding it later.
What should be planned before deploying an MCP server publicly?
Before public deployment, plan how the server will be tested against real client calls (not just unit tests), how errors are surfaced back to the calling model, and how the server will be monitored or versioned once other agents depend on it.