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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 LLMs to analyze logs by extracting patterns, redacting secrets, and providing token-efficient summaries from files, Docker containers, or journald.
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    Real-time GitHub Actions observability through VS Code with GitHub Copilot, providing DevOps metrics and interactive dashboards.
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    MIT
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    A Model Context Protocol server that enables LLMs to retrieve and analyze OpenTelemetry traces and metrics from Logfire, supporting exception tracking and custom SQL queries against telemetry data.
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    MIT
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    MCP server that exposes plugin crash reports from a crash reporting site to Claude, enabling querying and managing crash data via tools like listing frequent crashes, searching, adding comments, and managing plugins.
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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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    Enables querying sensors, devices, groups, channels, historical data, and system status from a PRTG Network Monitor instance via the classic PRTG HTTP API.
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    A TypeScript-based MCP server that enables users to interact with Prometheus metrics using PromQL queries and discovery tools. It allows LLMs to retrieve time-series data, metadata, alerts, and system status directly from a Prometheus instance.
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    Run NRQL, NerdGraph, and REST v2 operations to query data, manage incidents, create synthetics, and annotate deployments — all from your MCP client.
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    A read-only MCP server for Grafana Pyroscope that lets AI assistants query continuous profiling data, including flamegraphs, hotspot functions, memory allocations, and label discovery, directly from any MCP-compatible client.
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    A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.
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    Enables data observability operations with the Sifflet platform. Supports exploring assets, monitors, incidents, generating monitor-as-code YAML from descriptions, and performing impact analysis.
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    MIT
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    MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor.
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    MIT