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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 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.
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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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    Read-only VMware vCenter/ESXi monitoring. 8 MCP tools for VM inventory, host status, datastore capacity, cluster info, alarms, events, and VM details. Code-level enforced safety — no destructive operations exist in the codebase. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.
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    An MCP server that scans your lockfiles (npm, PyPI, Go, Rust, Ruby, PHP) for known vulnerabilities, enriches with EPSS exploit probability scores, and recommends fix versions. $14/mo — not per-seat.
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    MIT
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    AI-powered VMware vCenter/ESXi monitoring and operations. 20 MCP tools for inventory queries, health monitoring, VM lifecycle management, fast provisioning (Linked Clone, OVA, template deploy), snapshot management, and datastore browsing. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.
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    MIT
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    Enables searching and analyzing Sentry issues, events, and traces via natural language, providing tools for error investigation and distributed tracing.
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    Provides real-time visibility into Claude Pro and Max subscription usage limits directly within Claude Code by utilizing local OAuth tokens. It enables users to monitor session and weekly usage across different models and receive alerts regarding rate-limiting status.
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    Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.
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    This server acts as a MCP bridge to interact with the Cribl REST API. It allows AI models or other MCP clients to query and manage Cribl configurations.
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    Enables AI assistants to analyze weld photos for quality scoring and identify common defects like porosity or undercut. It provides practical bead-building tips and technical guidance for MIG, TIG, and Stick welding processes based on AWS/ASME standards.
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    Enables AI assistants to access Scout Monitoring performance and error data through Scout's API. Provides traces, errors, metrics, and insights for Rails, Django, FastAPI, Laravel and other applications to help identify and fix performance issues like N+1 queries, slow endpoints, and memory bloat.
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    Enables read-only Linux system diagnostics and troubleshooting on local and remote RHEL-based systems via SSH, including services, processes, logs, network, and storage analysis.
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    Provides tools to query and calculate AWS EBS performance metrics from CloudWatch, including IOPS, throughput, and latency. It also enables users to manage snapshots and retrieve advanced diagnostic data like I/O utilization and burst balance.
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    Provides access to real-time LLM pricing, speed metrics, and performance benchmarks for over 300 models from Artificial Analysis. It enables users to list, filter, and compare models based on costs, tokens per second, and intelligence indices.
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    Model Context Protocol (MCP) Server for Vunet vuSmartMaps - A multi-tenant observability platform integration. Query metrics, traces, logs, and data models from your Vunet tenants using natural language through AI assistants like Claude, GitHub Copilot, or any MCP-compatible client.
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    MIT
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    Enables language models to access LangSmith observability platform features including fetching conversation history, managing prompts, retrieving traces and runs, working with datasets and examples, and analyzing experiments.
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    An interface that allows large language models like Claude to interact with ActivityWatch time tracking data through the Model Context Protocol, enabling queries about application usage, browsing history, and productivity patterns.
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    MIT