MCP Server Neurolorap
by aindreyway
MCP Server Neurolorap provides tools for code analysis and documentation, allowing users to collect code and analyze project structure.
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What is MCP Server Neurolorap?
MCP Server Neurolorap is a server that provides tools for automated code analysis and documentation generation. It includes features for collecting code from projects and analyzing their structure, producing detailed reports in markdown format.
How to use MCP Server Neurolorap?
The server can be installed using uvx or pip. It can be used in developer mode with a JSON-RPC terminal interface or through MCP tools within a Python environment. It offers functionalities to collect code from specified paths and generate project structure reports.
Key features of MCP Server Neurolorap
Code Collection Tool with syntax highlighting and table of contents
Project Structure Reporter Tool with file size and complexity analysis
Developer mode with JSON-RPC terminal interface
Automatic dependency installation and Cline integration
Customizable ignore patterns using .neuroloraignore
Use cases of MCP Server Neurolorap
Automatically generate documentation for a software project
Analyze the structure and complexity of a codebase
Collect code snippets from a project for sharing or reference
Enforce code quality standards through automated checks
FAQ from MCP Server Neurolorap
How do I install the server?
How do I install the server?
Use uvx mcp-server-neurolorap or pip install mcp-server-neurolorap.
How do I run the server in developer mode?
How do I run the server in developer mode?
Use python -m mcp_server_neurolorap --dev.
How do I collect code from a specific directory?
How do I collect code from a specific directory?
Use the collect command in developer mode or the code_collector MCP tool.
How do I generate a project structure report?
How do I generate a project structure report?
Use the report command in developer mode or the project_structure_reporter MCP tool.
How do I customize which files are ignored during analysis?
How do I customize which files are ignored during analysis?
Create a .neuroloraignore file in your project root.