Skip to main content
Glama

Related Servers

Alternatives to bash-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to invoke common developer tools such as git, npm, Docker, and test runners and receive clean, schema-validated JSON instead of fragile terminal text, reducing token usage and parsing errors.
      0
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to work with developer tools such as git, npm, Docker, and test runners through structured, schema-validated JSON outputs. Reduces token usage and eliminates fragile terminal text parsing for reliable cross-platform workflows.
      0
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to invoke common developer tools — git, GitHub, npm, Python, cargo, Docker, Kubernetes, linters, and test runners — and receive schema-validated structured JSON instead of raw terminal text. This removes brittle string parsing and cuts token usage dramatically on verbose commands like builds, installs, and test runs.
      0
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to interact with common developer tools such as Git, npm, Docker, and test runners by returning schema-validated JSON instead of raw terminal text. This reduces brittle parsing errors and token usage while providing typed data agents can act on directly.
      0
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Wraps developer tools like git, npm, Docker, and test runners to return clean, schema-validated JSON instead of raw terminal text. This lets agents use typed, token-efficient results directly without brittle string parsing.
      0
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Provides MCP servers that wrap common developer tools such as git, npm, Docker, Kubernetes, and test runners, returning schema-validated structured JSON instead of raw terminal text. This lets AI agents consume typed, token-efficient results directly without brittle string parsing or platform-dependent formatting issues.
      0
      MIT

    TDQS

    B3.3/5.0

    Scored across 65 tools

    Disambiguation3/5

    Most tools target a distinct tool/resource (kube vs helm vs argo vs tf vs per-language lint/test), but several pairs are near-neighbors: find_files vs glob, git_diff vs git_diff_content, tf_state_list vs tf_show, and the cluster of '*_health_summary'/'*_failure_summary'/'*_diagnose' triage tools overlap conceptually with the plain getters they wrap. Descriptions do resolve most of these, but at 65 tools an agent must read carefully to avoid picking e.g. kube_get over kube_diagnose_pod when a diagnosis is wanted.

    Naming Consistency3/5

    Everything is snake_case, which is good, but the prefix/verb ordering is mixed: domain-prefixed noun-first (git_status, kube_get, tf_plan_summary, argo_app_diff) coexists with verb-first (list_guidance, check_environment, result_get) and bare Unix-style names (ls, tree, du, rg, glob, cat, jq, yq, run, batch). Readable, but not a single predictable pattern.

    Tool Count2/5

    65 tools is very heavy, even for a broad shell/devops toolbox spanning git, k8s, Terraform, ArgoCD, Helm, four language toolchains, and CI. Each tool is defensible in isolation, but the surface invites selection errors and could be consolidated (e.g. per-language lint/typecheck/test trios, summary vs getter variants).

    Completeness4/5

    Read/inspect coverage is deep across every advertised domain (files, git, Terraform, k8s, ArgoCD, Helm, CI, language toolchains), and run/batch act as an escape hatch for anything missing. Gaps are mostly write-side: no git mutations (commit/checkout/push), no kube apply/scale/exec, no file edit—though run largely works around them.

    Maintenance

    ActivityMaintained
    ResponsivenessSlow