XportL
by FastDrop
GPU fabric tools: NCCL benchmark analysis, degradation cost, cluster compatibility, XportL facts.
GPU fabric tools: NCCL benchmark analysis, degradation cost, cluster compatibility, XportL facts. Official MCP Registry: io.xportl/xportl@1.0.0. Remote endpoint: https://xportl.io/mcp
Problem it solves
Discoverable MCP server listed in the official MCP Registry.
How it's different
Remote MCP endpoint ingested from the official registry and probed by FastDrop.
Ingested from the official MCP Registry
FastDrop pulled this entry from the official MCP Registry as io.xportl/xportl and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed
and the description is not theirs.
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Read directly from the endpoint on 19 Oct 2026. Not supplied by the maker.
get_xportl_overviewReturns cite-ready facts about XportL from xportl.io: what it does, the problem it solves, the eBPF → ClickHouse → GNN → Rust enforcement architecture, supported fabrics/GPUs/collectives/kernels, use
analyze_nccl_benchmarkAnalyzes nccl-tests / rccl-tests results (paste raw all_reduce_perf output, or give size/busbw points). Detects node and GPU counts from the output, compares large-message bus bandwidth with the fabri
calculate_fabric_degradation_costEstimates what silent fabric degradation (slow NCCL collectives, flapping links, congestion) costs a GPU cluster: throughput lost, GPU-hours and dollars per year, idle-GPU equivalent, cost per degrade
check_cluster_compatibilityChecks a GPU cluster against XportL's published support matrix (Linux 5.8+ for eBPF, InfiniBand / RoCE v2 / NVLink, NVIDIA and AMD GPUs, NCCL / RCCL, on-prem / cloud / hybrid, host access for the eBPF
request_enterprise_demoSends the user's contact details and cluster summary to the XportL enterprise team to arrange a technical assessment or demo deployment. Before calling: collect name, work email, company and a summary
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