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    Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.
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    Orchestrates multiple AWS security services to provide comprehensive security assessments, threat analysis, and multi-framework compliance monitoring. It enables users to perform automated remediation recommendations and incident investigations through a unified Model Context Protocol interface.
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    Apache 2.0
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    Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.
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    MIT
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    Full-featured MCP server that exposes 36 tools for interacting with PostgreSQL databases, covering schema introspection, query execution, data exploration, performance monitoring, security auditing, and maintenance.
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    MCP server for Drumbeats monitoring. Enables creating monitors, triaging incidents, and running HTTP/SSL/DNS checks using natural language from any AI client.
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    Apache 2.0
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    Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.
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    MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.
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    GPL 3.0
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    eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime and Driver APIs via kernel uprobes and host events via tracepoints to build causal chains explaining GPU latency. 7 tools: get_check, get_trace_stats, get_causal_chains, get_stacks, run_demo, get_test_report, run_sql. Telegraphic compression reduces token usage ~60%. Supports stdio and HTTPS (TLS 1.3) transport.
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    Six-layer website monitoring (uptime, performance, SSL, DNS, visual regression, content change) from Claude, Cline, and Cursor. Free tools (DNS lookup, SSL check, speed test, website checker) work without an account; monitor, incident, alert, and status-page tools use a personal API key.
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    Zero-config MCP server that gives AI coding assistants a real-time diagnostic snapshot of your local dev environment. Detects framework, running services, recent errors, git state, and provides a health diagnosis in one call.
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    Enables users to access and manage Savri analytics data, including visitor statistics, traffic sources, and conversion funnels, directly within Claude. It supports tracking custom event properties and creating multi-step conversion goals through natural language prompts.
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    MIT
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    Estimates the environmental footprint of your AI use — energy (kWh), miles driven, water used for cooling, and CO₂ — plus a prompt-efficiency score, working with any AI client by measuring token usage.
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    Phoenix MCP Server is an implementation of the Model Context Protocol for the Arize Phoenix platform. It provides a unified interface to Phoenix's capabilites. You can use Phoenix MCP Server for: Prompts Management: Create, list, update, and iterate on prompts Datasets: Explore datasets, and synte
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    Apache 2.0
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    An MCP server that provides access to the Mixpanel REST API, enabling AI agents to query events, funnels, retention data, and user profiles. It allows users to perform complex analytics tasks and export raw event data through natural language prompts.
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    MIT
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    A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.
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