Neurolorap MCP Server

The MCP Server Neurolorap is a purpose‑built tool for developers who need to introspect, document, and audit codebases through an AI assistant. It solves the common pain of having to manually gather source files, generate documentation, and understand project structure—tasks that are repetitive yet critical for onboarding, code reviews, and compliance. By exposing its capabilities over the Model Context Protocol, the server lets Claude or other AI agents perform these operations on demand, turning static repositories into dynamic, AI‑friendly resources.

At its core, the server offers two powerful tools. The Code Collection Tool can traverse an entire repository or targeted directories, collate every file into a single Markdown document, and add syntax highlighting for any supported language. It also builds an automatic table of contents, making the resulting file easy to navigate and ready for inclusion in README files or knowledge bases. The Project Structure Reporter Tool analyzes the file tree, calculates metrics such as file size and complexity, and outputs a detailed Markdown report with visual tree diagrams. It even recommends refactoring opportunities and respects custom ignore patterns, allowing teams to focus on the most relevant parts of their code.

These tools are especially valuable in AI‑driven development workflows. For example, a Claude agent can be asked to “summarize the architecture of this project” and receive an instantly generated, up‑to‑date report. During onboarding, new contributors can request a quick code dump of the folder or an overview of test coverage. In continuous integration pipelines, the server can be invoked to produce audit‑ready documentation that accompanies each build. Because all interactions happen through MCP, the server integrates seamlessly with any AI platform that understands the protocol.

Neurolorap’s standout features include its zero‑dependency installation model—leveraging UV to automatically pull and configure everything—and a developer mode that exposes a JSON‑RPC terminal for debugging or manual use. The server’s output is Markdown by default, ensuring that the results are immediately consumable in documentation sites, wikis, or chat interfaces. Its ability to handle multiple languages and ignore patterns makes it adaptable to a wide range of project types, from monolithic Python backends to mixed‑language microservices.

In summary, the MCP Server Neurolorap empowers developers and AI assistants to turn code repositories into living documentation. By automating collection, analysis, and reporting, it reduces manual overhead, keeps documentation synchronized with the codebase, and provides AI agents with rich, structured insights that can accelerate development, onboarding, and quality assurance.