When you ask an AI coding agent to understand a C# solution, you quickly hit two problems: Text search is not semantic. Grep cannot reliably answer questions about symbols, types, overloads, or implementations. The agent burns context and time doing many small tool calls (search -> open file -> search again -> open file again). Glider MCP is my attempt to fix both. It is a Roslyn-powered Model Context Protocol (MCP) server that gives MCP clients (like Claude Code) compiler-grade understanding of your codebase: symbols, types, relationships, diagnostics, and safe refactors. ...
What is MCP? MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools. Core Architecture MCP Server: The component that exposes resources, tools, and prompts to the AI assistant. Servers can provide access to databases, APIs, file systems, or other external services. ...
Chat-assisted development is revolutionizing the way developers work by integrating AI tools directly into coding environments. These tools not only streamline the development process but also foster a more collaborative atmosphere. With an AI assistant handling repetitive tasks, offering code suggestions, and debugging issues, developers can dedicate more time to tackling complex problems and unleashing their creativity. The integration of AI in development environments brings numerous benefits. One of the most significant advantages is the reduction of time spent on mundane tasks. AI tools can automate code formatting, generate boilerplate code, and even suggest improvements based on best practices. This automation allows developers to focus on more critical aspects of their projects, such as designing innovative features and optimizing performance. ...