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    An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.
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    MIT
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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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    MCP server for Grubhub Data Platform operations, providing 40+ tools across 18 service categories for data platform management, observability, analytics, and collaboration.
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    A monorepo of MCP toolkits for Cloudflare Workers, providing over 630 tools across SaaS providers and AWS, with composite tools for security, incident response, billing, and cloud cost optimization.
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    MIT
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    Governed MinIO object-storage operations — capacity, exposure-surface audit, lifecycle, and healing RCA, with guarded bucket writes, unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.
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    MIT
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    Governs and automates network monitoring across SolarWinds Orion and Paessler PRTG platforms with a unified MCP server, enabling querying, alert management, and governed writes with audit logging.
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    MIT
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    Governed PostgreSQL DBA operations — slow-query, bloat, and blocking-lock RCA, index management, vacuum/analyze, and replication lag, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.
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    MIT
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    Governed MySQL + MariaDB DBA operations — slow-query, lock-wait/deadlock, replication, and fragmentation RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.
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    MIT
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    Patent-pending diagnostic + decisions-ledger engine for any host software system — operator briefs and a severity-gated MCP console.
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    Enables managing incident response workflows including incidents, on-call, postmortems, and more through the Runframe platform using MCP tools.
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    78
    4
    MIT
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    Enables querying and analyzing distributed traces from Jaeger, including service discovery, trace inspection, and performance analysis, through MCP tools.
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    Apache 2.0
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    PiPeFlow passively tracks AI agent workflow states using a finite state machine, providing tools for declaring, advancing, and auditing pipelines with annotations and reports.
    Last updated
    MIT