Skip to main content
Glama
alphaparkinc

genpark-edge-inference-latency-telemetry-skill

Official
by alphaparkinc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to genpark-edge-inference-latency-telemetry-skill

No user-submitted related servers found.

    Related Servers

    • genpark-edge-inference-latency

      Alpha-Park
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables profiling and optimizing edge and on-device LLM inference by measuring TTFT, TPOT, tokens/second throughput, and P50/P90/P99 jitter while providing standard-library primitives for quantization, paged attention, speculative decoding, and prefix caching.
      7
      MIT

    • metrillm-mcp

      MetriLLM
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables benchmarking of local LLM models (performance and quality) and sharing results to a public leaderboard via MCP tools.
      16 npm
      8
      Apache 2.0
    • genpark-kv-cache-paged-attention-allocator-skill by alphaparkinc

      genpark-kv-cache-pagedofficial

      alphaparkinc
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables MCP clients to manage LLM inference memory through virtual paged-attention KV-cache block mapping, non-contiguous physical page allocation, zero-copy fragmentation tracking, radix-trie prefix caching, INT8 quantized compute, and speculative decoding verification. It also exposes prefill and decode latency telemetry so edge deployments can be benchmarked and tuned without external dependencies.
      7
      MIT

    • InferBench

      RudrenduPaul
      A
      license
      Not graded
      quality
      A
      maintenance
      Vendor-neutral local LLM inference benchmark and hardware-config advisor for mlx and llama.cpp. Exposes an MCP tool that measures real tokens/second on your own hardware.
      10 npm
      Apache 2.0

    This server cannot be deployed

    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources