Alper Hoca MCP Server

The Next.js MCP Server is a lightweight, purpose‑built Model Context Protocol (MCP) service that turns any Next.js App Router project into a fully discoverable API catalog. By scanning the app’s file hierarchy, it extracts every route definition—paths, HTTP methods, parameters, and response schemas—and exposes this information through a standardized MCP interface. This makes it trivial for AI assistants to understand the shape of your backend, generate accurate prompts, and even suggest or validate API calls without manual documentation.

For developers building AI‑powered tools, this server solves a common pain point: the disconnect between code and natural‑language understanding. Traditional API documentation requires manual effort or external tools like OpenAPI generators. The Next.js MCP Server automates the entire process, delivering a JSON representation of all routes that can be queried on demand. The result is a living source of truth that keeps the AI’s knowledge in sync with your codebase, enabling features such as autocomplete for route names, parameter validation, and instant feedback on status codes.

Key capabilities include:

• Comprehensive route extraction – Detects all API routes in the app directory, including nested paths and dynamic segments.
• Method‑level metadata – Captures HTTP verbs, function signatures, and inline comments that serve as natural descriptions.
• Schema inference – Parses request bodies and status codes, providing a structured view of what each endpoint expects and returns.
• MCP‑compatible output – Serves data via a Server‑Sent Events (SSE) endpoint, ready for consumption by any MCP‑compliant client such as Claude or other AI assistants.

Real‑world scenarios that benefit from this server are plentiful. A product team can let an AI assistant walk through the entire API surface, generating documentation or testing scripts on the fly. A developer can rely on the MCP server to validate API calls during code reviews, ensuring that changes to route signatures are reflected immediately. In a continuous integration pipeline, the server can feed its output into automated tests or linting rules that enforce consistency across endpoints.

Integration is straightforward: once the server is running, AI workflows can query it via the standard MCP endpoint (). Because the data is structured and up‑to‑date, assistants can embed route information directly into prompts, create dynamic examples, or even trigger calls to the API during a conversation. The server’s focus on Next.js App Router projects gives it an edge in modern React ecosystems, where the file‑based routing system is a first‑class citizen.

In summary, the Next.js MCP Server bridges the gap between code and conversational AI by providing an automatically generated, machine‑readable map of your API. It empowers developers to harness AI assistants for documentation, testing, and real‑time code assistance, all while keeping the data tightly coupled to your source files.