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    Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2
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    54
    50
    MIT
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    Enables comprehensive integration with Azure AI services including OpenAI, Cognitive Services, Computer Vision, and Face API through a mission-critical MCP server. Provides enterprise-grade reliability with high availability, observability, chaos engineering, and secure multi-region deployment capabilities.
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    MIT
  • F
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    Unified local MCP AI Gateway that routes across Groq, OpenRouter, Mistral, and local Ollama providers, with OpenAI-compatible APIs, MCP tools, fallback/racing router, monitoring, and web dashboard.
    Last updated
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    A unified local API gateway providing caching, rate limiting, and full Model Context Protocol compatibility for AI agent integration. It enables users to aggregate multiple API endpoints into a single gateway with built-in observability and customizable eviction strategies.
    Last updated
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    Unofficial MCP server for Vexo analytics. Enables querying event names, counts, timelines, sessions, and recent events from Vexo Export API through natural language.
    Last updated
    6
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    MIT
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    Model Context Protocol server for Verlon AI that exposes gates, logs, recommendations, and experiments as MCP tools, enabling coding agents to inspect and manage AI infrastructure natively.
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    5
    350
    MIT
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    Read-only MCP server for Umami analytics. It talks to the Umami REST API directly over HTTP, supporting self-hosted and cloud setups.
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    MIT
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    Enables causal root cause analysis with 55 tools covering causal graph construction, 13 RCA model families, multi-model consensus, and report generation. Works with 9 LLM providers including Claude, Ollama, and OpenAI.
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    56
    MIT
  • F
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    Provides tools for AI assistants to manage and diagnose MWAA Airflow environments, EMR Serverless jobs, S3 files, and Confluence documentation. It features automated pipeline failure diagnosis and comprehensive log retrieval across these integrated platforms.
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    44
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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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    9
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    A Model Context Protocol server that provides tools to interact with Matomo Analytics API, enabling management of sites, users, goals, segments, and access to analytics reports through a MCP interface.
    Last updated
    11
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    ISC