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

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    Blocks dangerous operations: rm -rf, sensitive file access, privilege escalation, and more are denied before execution. Gates risky commands behind human approval (optional): configurable commands require explicit operator sign-off via a web GUI before the agent can proceed. Simulates blast radius: wildcard operations like rm \*.tmp are evaluated against real files before running, and blocked if th
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    MIT
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    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.
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    A Model Context Protocol server focused on China's A-share stock market that provides data on stocks, financials, market indices, and macroeconomic indicators.
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    MIT
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    Enables LLM agents to execute arbitrary Python code in secure, isolated sandbox environments with automatic dependency management and file handling. Each code execution runs in a fresh virtual environment that gets destroyed after completion, providing safe and reproducible Python code execution.
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    MIT
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    One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose
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    MIT
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    An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.
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    ISC
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    Official MCP server for Shipmail, enabling agents to manage domains, mailboxes, messages, threads, webhooks, and suppressions via natural language.
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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    MIT
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    A cloud gateway that dynamically parses standard OpenAPI JSON specifications and provisions a hosted, remote Model Context Protocol (MCP) server running over Server-Sent Events (SSE).
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    MCP server for verifying AI agent claims vs reality — single-transcript inline grounding-check that flags when an agent's response states facts not in the input context, when its code silently swallows exceptions and substitutes mock data, or when its multi-turn transcript contains contradictions or unverified completion claims. Sub-second, local, free, no API calls.
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    Intelligence layer for AI that enables querying across revenue, errors, identity, and analytics layers in plain English, returning rendered charts and dashboards.
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    MIT
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    A source-grounded memory layer for AI agents that stores, links, and recalls factual memories with confidence levels and citations, enabling honest answers when information is not in the record.
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    MIT
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    A streamlined MCP server that enables AI assistants to send real-time notifications to your devices through the ntfy service, allowing you to receive alerts when tasks complete or important events occur.
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    GPL 3.0