Incremental Context Loading

What problem does it solve?

Traditional code exploration and architecture analysis consume excessive tokens by reading whole files. Incremental Context Loading reduces token usage by loading context progressively using MCP-first techniques, enabling faster insights with less data.

Core Features & Use Cases

• MCP-first discovery: Build a layered understanding of codebases using small, fast MCP queries.
• Targeted symbol loading: Load only relevant symbols and their bodies when needed to modify or audit.
• Aggressive pruning: Remove irrelevant context after each stage to maximize token efficiency.
• Use case: When exploring unfamiliar repositories, quickly determine the most impactful area to inspect and implement changes with minimal context.

Quick Start

Trigger incremental loading by first using MCP overviews to map the codebase, then progressively load targeted symbols and prune unused context as you work.