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

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Bridges Xcode and Cursor to provide real-time access to build errors, warnings, and debug output from Xcode's DerivedData, enabling automated error analysis and fixes directly within Cursor.

Linux sandboxes for AI agents, each a Firecracker microVM. Run code, keep files, pause and wake with memory kept, snapshot and fork.

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.

Enables AI agents to safely control a browser through MCP by enforcing deterministic policies, keeping secrets out of model context, and requiring human confirmation for risky actions.

Enables AI agents to search, read, and traverse a local knowledge base of Markdown files using full-text search and relationship graph, reducing token usage.

Enables MCP clients to serve and query semantic models, providing tools for entity descriptions, metric lookups, context resolution, and operation validation for AI agents.

A high-performance MCP execution engine that runs tool code in isolated, resource-constrained sandboxes with context state persistence.

Enables agents to safely drive a simulated Franka Panda pick-and-place cell through MCP tools, with gated motion, emergency stop, structured errors, and audit logging.

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 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.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

A robust runtime for the official Model Context Protocol (MCP) that adds proxying, session management, JWT auth, persistent user storage with scopes, and progress notifications.

A shared runtime that discovers LangChain tools from a toolset package and serves them as an MCP server, with optional UI views and a CLI for managing tools.