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    Enables checking IP reputations and threat intelligence by querying Chaitin's global honeypot network and millions of defense nodes. Provides real-time IP profiling, malicious behavior detection, and threat alerts based on aggregated security data.
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    MIT
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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
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    Apache 2.0
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    A Model Context Protocol server that enables AI assistants to interact with Kubernetes clusters through natural language, supporting core Kubernetes operations, monitoring, security, and diagnostics.
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    MIT
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    Enables AI agents to diagnose Linux server incidents by collecting and structuring system diagnostics from multiple servers via SSH, with tools for finding incident clusters, gathering context (memory, CPU, swap, etc.), and running arbitrary commands.
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    A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.
    Last updated
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    Real-time status monitoring, uptime tracking, incident history, and API pricing for 42+ AI tools including ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, and Groq. No API key required. Data updated every 5 minutes from independent monitoring infrastructure.
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    MIT
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    A comprehensive Linux system performance profiler with MCP remote invocation support, featuring advanced process profiling and flame graph generation.
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    Apache 2.0
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    An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.
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    MIT
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    Voice-powered bug reporting MCP server with 13 tools. Captures console logs, network errors, DOM traces, and developer voice descriptions. AI reads structured reports to find and fix bugs automatically. Chrome Extension + Python CLI.
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    MIT
  • F
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    An MCP server that monitors 12 Australian SMB intelligence sources to analyze market signals and provide structured data for content strategy agents. It enables users to track regulatory changes, AI trends, and business data through automated signal grading and Slack integration.
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    Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.
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    MIT
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    Enables AI agents to self-report bugs, ambiguities, and improvement requests via a single report_issue tool, logging to PostgreSQL or JSONL with severity and mode classification.
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    LGPL 3.0
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    Enables checking and validating disk space usage via a single tool, reporting total, used, and available space with optional free space thresholds.
    Last updated
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    MIT
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    A pre-action risk gate for AI agents. Your agent calls the forecast tool before any irreversible action — send email, run SQL, make a payment, delete a file — and gets a risk score (0–100) and a GO / CONFIRM / STOP verdict in a few seconds.
    Last updated
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    146
    MIT