Alexwohletz Language Server MCP

Overview

The Alexwohletz Language Server MCP is a TypeScript‑based Model Context Protocol (MCP) server that brings traditional language‑server capabilities—hover information, code completion, and diagnostics—to AI assistants such as Claude. By exposing these features through MCP tools, the server allows an assistant to query real‑time code intelligence while a developer is editing files in any supported editor or IDE. This integration eliminates the need for separate tooling, letting the assistant act as a single source of truth for code analysis.

The server solves a common pain point: developers often juggle multiple plugins or services to get instant feedback on their code. With MCP, the assistant can request hover text for a symbol, receive completion suggestions at a specific cursor position, or pull diagnostic errors and warnings—all through a simple JSON payload. The assistant can then surface that information directly in the editor or within conversational responses, creating a seamless, context‑aware coding experience. Because the server is written in TypeScript and has already been tested with the TypeScript language server, it provides robust type‑checking and accurate suggestions out of the box. The architecture is designed to be extensible, with a clear contract for adding support for other languages like Python or custom language servers.

Key capabilities include:

• Hover Tool () – Returns documentation or type information for a symbol at a given line and character.
• Completion Tool () – Supplies context‑sensitive code completions, enabling autocomplete suggestions that respect the current file’s state.
• Diagnostics Tool () – Emits errors, warnings, and informational messages, allowing the assistant to highlight problematic code sections.
• MCP Integration – Implements full MCP communication, so clients can discover and invoke these tools via standard protocol messages.
• Language Agnosticism – While currently focused on TypeScript, the server’s design encourages adding additional language servers with minimal friction.

Real‑world scenarios benefit from this setup: a developer typing in Visual Studio Code can ask the assistant for a quick explanation of an unfamiliar API, receive autocomplete suggestions without leaving the conversation, or trigger a diagnostics run that surfaces all linting errors inline. In pair‑programming setups, the assistant can act as a silent partner that continuously monitors code quality and offers instant feedback. Because MCP servers communicate over standard input/output, the server can be launched from any environment that supports Node.js, making it easy to integrate into CI pipelines or cloud‑based IDEs.

Unique advantages of the Alexwohletz Language Server MCP lie in its tight coupling between AI assistants and language‑server features. Unlike generic LSP plugins that require separate configuration, this MCP server exposes all functionality as first‑class tools within the protocol. Developers gain a single, lightweight entry point to advanced code intelligence, while AI assistants can leverage that intelligence without the overhead of maintaining separate language‑server instances. This approach streamlines workflows, reduces context switching, and ultimately speeds up development cycles by providing on‑demand, AI‑powered code insights directly within the editing environment.