"MCP server for building and debugging VSCode extensions" matching MCP servers:

Enables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.

Exposes PICO XR building blocks as MCP tools, enabling AI agents to programmatically configure XR scenes for PICO devices through idempotent, non-destructive operations.

MCP server to expose VS Code editing features to an LLM for AI coding

A portable MCP server enabling AI assistants to operate VS Code, including file management, extension control, and workspace automation.

Enables AI agents to control VSCode workspaces, including file operations, terminal commands, search, and workspace management.

Enables AI agents to programmatically control and automate VSCode by interacting with its UI, executing commands, and inspecting the DOM structure. It supports advanced workflows like UI testing, extension development, and debugging through a standalone VSCode instance.

Provides intelligent error detection and debugging capabilities across multiple programming languages with real-time monitoring of build, lint, runtime, console, and test errors. Offers AI-enhanced error analysis with automated resolution suggestions and context-aware debugging.

Connects VSCode with MCP to provide AI assistants real-time access to LSP diagnostics, symbol info, and code navigation, enabling efficient code analysis without slow build commands.

Enables AI agents to access VS Code's LSP-based code navigation and native debugging tools (definitions, references, outline, breakpoints, stepping, stack frames, variables, and evaluate) via the MCP protocol.

Gives AI agents full control of VS Code's debugging engine — set breakpoints, launch/attach sessions, step through code, inspect call stacks and variables, and evaluate expressions in the paused frame.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Exposes VSCode Jupyter notebooks to MCP-compatible AI agents, enabling them to read, edit, and run cells against the same kernel.

Converts VSCode into an MCP server that enables external clients to remotely execute VSCode internal commands, query workspace information, and interact with the editor through HTTP streaming. Built on the FastMCP framework with security controls and real-time monitoring.

A Model Context Protocol (MCP) server that provides VSCode context and filesystem operations for AI assistants.

MCP server that wraps STM32CubeMX CLI to let AI load .ioc projects, modify pin/peripheral configurations, generate HAL code, and export pinout tables.

VS Code Extension & Model Context Protocol Suite Orchestrator for Cursor, Claude Desktop, and VS Code IDEs.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Exposes VS Code's Debug Adapter Protocol as MCP tools, enabling AI coding agents to set breakpoints, step through code, inspect variables, and read exceptions in a real debug session.

Exposes Jupyter notebook operations as MCP tools over plain HTTP, allowing AI agents to explore, edit, run, and debug notebooks in a live VS Code session using local or remote kernels.

A lightweight bridge extension that enables Claude Desktop to connect to VSCode workspaces via Model Context Protocol, allowing Claude to read and write files, create directories, and list contents in your workspace.