netlab-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables LLMs to plan, validate, generate, and deploy Cisco Packet Tracer network topologies from natural-language prompts, including routing, switching, DHCP, VLANs, security, IPv6, wireless, live deployment, verification, and .pkt project management.3MIT
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- AlicenseNot gradedqualityCmaintenanceEnables 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
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to explore, build, run, and troubleshoot Cisco Modeling Labs (CML 2.x) network topologies, including lab construction from specs, console command execution, reachability testing, packet capture analysis, link impairment scenarios, and topology diagram export.MIT
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: topology generation, known-good retrieval, host check, example listing, compatibility query, config rendering, failure reporting, and lab validation. No overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., generate_topology, validate_in_lab, report_failure). Naming is predictable and readable.
With 8 tools, the set is well-scoped for a netlab MCP server. Each tool is justified and covers a specific step in the workflow without being excessive or insufficient.
The tool surface covers the full lifecycle: topology generation, config rendering, validation, host readiness, compatibility queries, failure reporting, and example browsing. No obvious missing operations for the intended domain.