Think Different

When executing multi-file refactors, I manage, restrict, and structure my local codebase context using a strict hierarchical filtering system designed to maximize accuracy and minimize token waste. Here is exactly how I structure and execute that process: 1. Discovery and Map Generation Before reading or editing any files, I construct an abstract map of the codebase. I do not pull full source code at this stage. Directory Trees: I run a shallow directory listing to understand the project's layout. Symbols and Signatures: I search for class definitions, method signatures, and export statements across the target modules. Dependency Graphs: I map out how the target files import one another to identify the upstream and downstream impacts of the refactor. 2. Context Restriction (The "Need-to-Know" Filter) To prevent token bloat and LLM confusion, I categorize files into three strict isolation zones: The Edit Zone: These are the exact files that require code modifications....

                                                                       MCP server from research gate An MCP server, or Model Context Protocol server, acts as a bridge, enabling AI models to interact with external tools and data sources through a standardized interface. It simplifies the process of connecting AI applications to various services and resources, making it easier for developers to build and deploy AI-powered applications.  We all have tons of API services and servers already. However now due to AgenticAI and multiple Agent applications with MCP. It is getting difficult if not totally impossible to connect the same API services. So I thought, how can we convert our existing API services into MCP capable. This guide provides a complete end-to-end solution for conver...

                                                                                 image from Google next To break down "MCP" and "MCP tools": Model Context Protocol (MCP): This is an open standard that aims to standardize how Large Language Models (LLMs) communicate with external applications, data sources, and tools. Essentially, it provides a structured way for LLMs to interact with the "outside world" in a consistent manner. It follows a client-server architecture, where: MCP clients (like LLM applications) request actions. MCP servers provide access to tools and data. MCP Tools: These are the specific functions or capabilities that MCP servers expose. They allow LLMs to perform actions, such as: Accessing files. Interacting with ...