Skip to main content
Glama

Related Servers

Alternatives to Netdryrun

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables read-only verification of SR Linux and FRR network-device command output without device credentials, turning raw text into structured verdicts about interfaces, routes, BGP peers, and overall health. It also sanitizes that untrusted output by masking secrets and neutralizing prompt injection before a model reads it.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI-assisted management of multi-vendor network devices (Cisco, Juniper, Nokia, Arista, Linux) through natural language, supporting health checks, configuration changes, routing analysis, and automation workflows.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to directly inspect, configure, test, and orchestrate network devices through pyATS/Genie, including show command parsing, config rollback, feature state learning/diffing, fleet-wide command fan-out, and declarative test execution.
      MIT

    TDQS

    A4/5.0

    Scored across 7 tools

    Disambiguation4/5

    dry_run and start_run perform the same operation (sync vs async) and get_result is tightly coupled to start_run, but the descriptions make the relationship and polling flow explicit. run_checks could be mistaken for dry_run, yet its description clearly states it reuses an already-running lab without deploy/destroy. Boundaries are mostly distinct with only this intended pairing overlap.

    Naming Consistency4/5

    Six of seven names follow a verb_noun pattern (dry_run, start_run, get_result, run_checks, record_baseline, check_types). 'validate' is a bare verb, a minor deviation, but the overall convention is predictable and readable.

    Tool Count5/5

    Seven tools is well-scoped for a dry-run validation server: a synchronous path, an asynchronous path with polling, a re-check tool, baseline generation, and two lightweight metadata/introspection tools. Each earns its place.

    Completeness3/5

    Core lifecycle (validate, dry_run, async run + poll, run_checks, record_baseline, check_types) is covered, but the keep_lab=true flow explicitly tells the agent to 'destroy the lab' afterward and there is no destroy_lab or list_runs tool to do so. That is a notable dead end in a workflow the descriptions actively encourage.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues