"Debugging WebRTC SDK Implementation Issues in Visual Studio 2019" matching MCP servers:

Studio MCP transforms any CLI command into an AI tool by using a simple template syntax to define input schemas and arguments. It enables AI agents like Claude and Cursor to execute local scripts and system commands through a dynamically generated Model Context Protocol server.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

MCP server for Decky Loader plugin development, providing tools to build, deploy, debug, and capture screenshots/recordings on a Steam Deck via commands like deck.deploy and deck.captureScreenshot.

Scaffolds stateless MCP servers with explicit state handles, a pluggable state store, and a visual inspector for debugging.

A cross-platform screenshot tool that lets coding agents capture and view their output, enabling self-correction through visual feedback.

Enables AI assistants to manage remote servers via SSH with 14 commands for execution, file transfer, auditing, and monitoring.

Enables LLMs to perform live debugging, dump analysis, and remote debugging by exposing Microsoft CDB capabilities through MCP. It manages cdb.exe sessions, forwards commands, and returns raw debugger output.

Provides structured debugging capabilities through LLDB, enabling AI assistants to set breakpoints, inspect variables, analyze crashes, disassemble code, and evaluate expressions in C/C++ programs.

A stdio MCP server that lets Codex Desktop/CLI delegate implementation tasks to Claude Code CLI with workspace validation, Git status checks, and session resume capabilities.

Enables secure remote command execution and file operations over SSH/SFTP with automatic authentication resolution. Features built-in diagnostics that identify connection issues—such as stale host keys, unloaded agents, or permission errors—and provide specific commands to fix them.

Stop Package Chaos: Unveil Your Mac’s Setup for Targeted ML Debugging

Checks your local development environment for common issues like wrong Node version, missing Docker, missing git config, missing .env keys, and busy ports, and provides fixes.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables programmatic control over tmux terminal sessions for SSH access, command execution, and terminal automation. Supports creating sessions, sending commands, capturing output, and managing multiple panes for interactive debugging and monitoring.

An environment diagnostic and correction tool for MCP that provides detailed system insights, runtime checks, and actionable suggestions to fix common issues.

Provides intelligent command completion, validation, and contextual help for the Kafka Docker Playground CLI. Integrates with GitHub Copilot to offer auto-complete suggestions, detailed command assistance, and debugging support for playground operations.

A Model Context Protocol server implementation that enables secure remote command execution via SSH, with features for managing and using SSH credentials.

Headless local stdio MCP server for board-debug operations, allowing compatible clients to use tools for firmware debugging and board management.

A lightweight MCP server that enables LLM agents to interact with GDB for debugging native programs, supporting spawning sessions, executing commands, interrupting hangs, and closing sessions.

Enables crash dump analysis and kernel debugging by integrating the real crash utility with automatic dump discovery, kernel matching, and session management.