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Related Servers

Alternatives to Cloud DevOps MCP Server

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides Kubernetes deployment intelligence with typed query tools and AI-synthesized risk briefs, enabling users to list workloads, get detailed snapshots, query Prometheus metrics, record deployment history, and generate risk assessments before promoting to production.
      25 PyPI
      Apache 2.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables AI coding assistants to check whether an API key is safe to expose, audit Supabase Row Level Security, generate owner-based RLS policy templates, and run a builder-specific pre-launch security checklist. Runs locally over stdio with no network calls, telemetry, or file access.
      5
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables Claude to audit AI/ML projects for production readiness through deterministic static analysis, check ML system descriptions, compare model configurations, and generate readiness reports or deployment checklists. It returns scored, evidence-based findings with explicit unknowns while never executing submitted code or accessing the network.
      Apache 2.0

    TDQS

    A4.4/5.0

    Scored across 12 tools

    Disambiguation4/5

    Descriptions explicitly cross-reference paired tools (e.g., review_iam_policy vs review_cloud_identity_policy, review_terraform_security vs assess_terraform_change), helping agents distinguish them. However, the set includes several adjacent 'review_' tools (Kubernetes deployment vs security, GitHub Actions vs generic CI/CD) that could still cause hesitation without careful reading.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern using assess_, build_, estimate_, and review_ prefixes. No naming inconsistencies or mixed conventions are present.

    Tool Count5/5

    With 12 tools, the set sits comfortably within the ideal 3–15 range. Each tool targets a distinct domain or analysis type, and no tool appears redundant.

    Completeness4/5

    The surface covers major DevOps analysis domains: Terraform change and security, cloud change bundles, CI/CD and GitHub Actions, IAM and cloud identity, Kubernetes deployment and security, SLO budgets, incident runbooks, and supply chain. Some gaps exist (e.g., cost optimization, compliance, or actual remediation), but the server explicitly scopes itself as analysis-only, so coverage is strong for that purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues