How to Build an MCP Server Without Writing Code

Route 1: generate from an API specification

If the system you want to connect already has an OpenAPI specification, several tools can turn it into an MCP server directly. Each operation becomes a tool, parameters become input schemas, and descriptions come from the spec.

What it gets right. It is fast and faithful to the API. If the spec is accurate, the tools work.

What it gets wrong. One tool per endpoint produces a large, repetitive catalogue. An API with eighty operations becomes eighty tools, most of which the agent will never need, all of which cost context. Spec descriptions are written for developers reading reference docs, not for a model choosing between similar options.

Fix it by selecting only the operations the agent should use, and rewriting their descriptions to say when to use each one.

Route 2: expose workflows from an automation platform

Workflow automation platforms increasingly let you publish a workflow as an MCP tool. You build the workflow visually: take inputs, call a service, transform the result, return it. The platform handles hosting, credentials, and the MCP endpoint.

What it gets right. Credentials stay in the platform rather than in the agent's configuration. Each tool can do several steps, so the tool matches a task rather than an endpoint. Non-developers can build and maintain them.

What it gets wrong. Error handling is often an afterthought, and a workflow that fails silently returns something the agent will treat as a real answer. Latency can be high for multi-step flows.

Fix it by returning explicit errors and keeping each workflow to one clear job.

Route 3: have a coding agent write it

Describe the server to a coding agent: what system it connects to, which tasks it should support, what it must never do. Ask it to use an official MCP SDK, write tests, and run them. The agent produces a real codebase you did not have to write.

What it gets right. You get exactly the tools you asked for, shaped around tasks, with clean descriptions and tests.

What it gets wrong. It is still code. Someone must host it, update dependencies, and read it well enough to trust its handling of credentials and inputs. No-code for the author is not no-maintenance for the team.

The decisions no route makes for you

Which tools exist. Start from the tasks the agent should perform, not from what the system exposes. Five task-shaped tools beat fifty endpoint-shaped ones.

How they are described. The model picks tools by reading descriptions. Say what each does, what it needs, and when to use it instead of its neighbours.

What is read and what is write. Start read-only. Add write tools one at a time, and put destructive operations behind confirmation or leave them out.

Whose credentials. A server acting with an administrator's token gives every agent session administrator power. Use a dedicated identity with the narrowest permissions that work.

How big the responses are. A tool that returns an entire record set floods the agent's context. Paginate and return only the fields that answer the question.

When you may not need a new server at all

Many teams build a server to let an agent answer questions about internal material: documentation, policies, specs, past decisions. That is a retrieval problem, not an integration problem. Indexing the material and connecting an existing retrieval server gives the agent searchable access without building and maintaining a custom server for each source.

Build custom servers for actions and live data. Use retrieval for knowledge. The split also keeps each custom server small, which makes it easier to secure and to review.