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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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    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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    MIT
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    Enables management and monitoring of farm operations including field and crop tracking, livestock monitoring, equipment management, and sensor readings through a Model Context Protocol interface built with FastMCP.
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    Enables interaction with Cumulocity IoT platform for device management, measurements, and alarm monitoring. Supports filtering devices, retrieving measurements with time-based queries, and accessing active alarms through natural language.
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    Apache 2.0
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    Connects AI coding assistants to Shipbook for investigating issues using real application logs with error classification, log search, and session tracing.
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    MIT
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    Enables AI assistants to interact with Enmask data masking tool via MCP tools for health checks, connection management, schema inspection, and job monitoring.
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    MIT
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    Enables interaction with Sentry's error tracking and monitoring tools through a unified API, allowing natural language access to Sentry services.
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    MIT
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    Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.
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    Apache 2.0
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    Small production-oriented MCP server for diagnosing incidents from Elasticsearch logs with unknown schema. It provides tools for log discovery, retrieval, and issue diagnosis.
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    MIT
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    Enables interaction with InfluxDB v3 (Core/Enterprise/Cloud Dedicated) through MCP clients. Supports database management, data querying and writing, schema inspection, and token administration operations.
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    MIT
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    Enables AI assistants to query Prometheus metrics, monitor alerts, and analyze system health through read-only access to your Prometheus server with built-in query safety and optional AI-powered metric analysis.
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    MIT
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    Enables real-time data streaming through Server-Sent Events with timestamp broadcasting and server monitoring capabilities. Optimized for deployment on Render.com with health checks and status endpoints.
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    Provides a standardized MCP interface for querying Graylog logs, enabling AI agents to search, diagnose, and correlate runtime logs with code via configurable profiles.
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    MIT