"How to identify when runtime errors occur in a program" matching MCP servers:

A unified developer toolkit for AI-assisted workflows. Task timing, doc drift detection, env validation, secret scanning, port conflict resolution, AI context generation, and license auditing — one MCP server, one install.

Enables building and flying rockets in Kerbal Space Program 1.x via MCP, providing editor, flight control, and real-time telemetry tools without requiring visual input.

Aziel Runtime is a node-meshed MCP software orchestration suite for digital forensics, auditing, provenance, research, intelligence-support, and secure agent workflows, with a single gated execution path, compartmentalized engines, verifiable receipts, temporal integrity, and explicit capability refusal. It is not merely an API aggregator or generic tool router.

MCP server that wraps the Apify Workplace Program Detector actor, taking a company domain and returning the employee programs it publishes, such as ERGs, DEI, wellbeing, parental leave, and volunteering.

An MCP server that makes AI agents speak a brief summary of every response out loud using TTS.

Enables AI coding agents to compile, test, run, hot-swap, and debug Java applications incrementally through MCP, providing runtime feedback for verifying code changes.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

Provides AI coding agents with real-time visibility into local development runtime state, enabling them to tail application logs, inspect ports, monitor process metrics, and diagnose network errors.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Private TypeScript runtime for a shadow-first AI operating system and company operating intelligence layer for HVAC, plumbing, electrical, sewer, and cross-trades businesses.

A local, evidence-driven MCP runtime and control plane for open-source maintainers that provides workspace-bounded tools including controlled file operations, command execution, validation primitives, durable execution records, and human review workflows via stdio and Streamable HTTP transports.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

MCP server for amazon.in — cheapest in-stock, best-value picks, and price history links.

A TypeScript MCP server that lets AI assistants interact with the Godot 4.x game engine: not just editing files, but playing the game.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

ai-runtime-guard is an MCP server that sits between your AI agent and your system, enforcing a policy layer before any file or shell action takes effect. No retraining, no prompt engineering, no changes to your agent or workflow, just install, configure once, and your agent operates within the boundaries you set.