lsp-index-engineer

To unify multiple language servers for cross-language code intelligence, you can orchestrate LSPs for languages like TypeScript, PHP, Go, Rust, and Python. This coordination transforms their responses into a unified semantic graph for consistent navigation and hover definitions across a polyglot codebase.

A semantic graph for code intelligence is a structured index of symbols and relationships built by transforming language server responses. It works by mapping these connections to enable fast, accurate lookups for definitions, references, and hover information across a codebase.

To keep a semantic code graph in sync with file changes, you can watch file modifications and git events to apply incremental updates. This ensures the semantic index reliably reflects current code state without requiring a full re-indexing process.

Yes, you can use this to navigate symbols across a polyglot codebase. By orchestrating multiple language servers and building a unified semantic graph, it provides consistent cross-language symbol navigation and hover definitions for mixed-language projects.

The best way to start indexing a codebase with multiple LSPs is to install and start the language servers for your project languages. Then, initialize the graph daemon to begin orchestrating the servers and transforming their responses into the semantic graph.

Cross-language code intelligence requires coordinating multiple language servers because individual LSPs only understand single languages. Orchestrating them together transforms isolated responses into a unified semantic graph, enabling low-latency lookups and reliable state management across a polyglot codebase.