Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.
Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.
Wraps the Eclipse JDT Language Server to enable AI assistants to understand Java codebases, search symbols, navigate definitions/references, and read third-party .class files.
Bridges the Model Context Protocol with Language Server Protocol to provide AI agents with persistent access to code intelligence features including navigation, diagnostics, refactoring, and completion across 7+ programming languages.