co.fastgpu/fastgpu

Est-ce que co.fastgpu/fastgpu est sûr ?

Au dernier audit MCP Hub, le serveur MCP « co.fastgpu/fastgpu » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.

Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.

Les 2 outils

• list_gpu_prices≈ 698 tokens

  One entry per GPU model with its cheapest live on-demand cloud rental price in USD per GPU-hour, the provider offering it, and how many providers rent it, from FastGPU's live price feed across marketplaces, neoclouds and hyperscalers (RunPod, Vast.ai, Lambda, AWS and more). Use it to compare GPU rental prices or to find where a named GPU is cheapest to rent. Each price is the provider's own per-GPU rate: cheapest_min_gpu_count says when it is only sold as a multi-GPU instance, and cheapest_billed_separately names what the provider bills on top of it (CPU, memory, storage), null when the rate includes CPU and memory. page_url links to the GPU's live price page with every offer. Rental prices only: it does not rent, reserve or launch GPUs. No key required.

  Paramètres, retour & exemple (2)

  Paramètres

  • tier · string · optionnel · flagship | datacenter | prosumer | entry
    Return only one class of GPU (case-insensitive; combines with vendor). flagship: the current top training and inference accelerators (H100, H200, B200, GB200, MI300X, MI355X). datacenter: earlier or mid-range data-center and workstation cards (A100, L40S, L4, A10, RTX 6000 Ada, V100, MI210). prosumer: desktop consumer and workstation cards (RTX 5090, RTX 4090, RTX 3090, RTX A4000). entry: small inference cards (T4, A2, A16, P4). Omit for every tier.
  • vendor · string · optionnel · NVIDIA | AMD
    Return only GPUs made by this vendor (case-insensitive). Combines with tier: both must match. Omit for every vendor.

  Exemple d'appel

  {"name": "list_gpu_prices", "arguments": {"tier": "flagship", "vendor": "NVIDIA"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"gpus": [], "count": 1, "stale": true, "updated_at": "texte"}}

• match_workload≈ 2447 tokens

  Ranks up to eight GPU configurations that can run a job at the lowest live price. Describe the job in query (an open-weight model to serve or fine-tune, a model size, or a GPU need) or with the structured fields. Each match gives the GPU count, the USD per hour for the whole configuration and a one-line reason; the answer also states the VRAM the job needs and how much cheaper the top match is than a hyperscaler running the same job. Use it to decide where to run a workload; use list_gpu_prices for the price of a named GPU. Open-weight models only: an API-only model such as GPT-4 returns no matches and a note. Between otherwise equal offers, a small disclosed tie-break favors providers that pay FastGPU a referral (each match reports partner). Hard limits (budget_usd_hr, max_total_usd with duration_hours, max_quote_age_minutes) drop every configuration that breaks them; limits reports what was dropped. Read-only: it does not rent or launch GPUs. No key required.

  Paramètres, retour & exemple (16)

  Paramètres

  • spot · string · optionnel · true | false
    Set true to include interruptible spot capacity for a cheaper rate.
  • task · string · optionnel · inference | finetune-lora | finetune-full | generate | transcribe | embed
    What the job does.
  • model · string · optionnel
    Open model name to size against, e.g. "Llama 3 70B", "Qwen 72B", "Mixtral".
  • query · string · optionnel
    Plain-language job, e.g. "cheapest to serve Llama 3 70B", "2x H100 for fine-tuning" or "a GPU with 80GB of memory". Provide this OR a structured spec below.
  • region · string · optionnel · US | EU | ASIA
    Restrict to a data-residency region.
  • vram_gb · integer · optionnel
    Rough VRAM the job needs, in GB, if you already know it.
  • params_b · number · optionnel
    Model size in billions of parameters when no exact model is named.
  • reserved · string · optionnel · true | false
    Set true to include reserved / committed-term capacity for a lower rate.
  • gpu_count · integer · optionnel
    Exact positive GPU count. Overrides a count in query text. Returns no matches if no supported configuration fits; omit for automatic sizing.
  • precision · string · optionnel · fp16 | int8 | int4
    Numeric precision to size the model at.
  • weights_gb · number · optionnel
    Measured size of the weights as stored, in GB: the file you will load (for example a GGUF Q4_K_M build, which holds more bits per parameter than its nominal 4). Replaces parameters times bytes per parameter in the memory estimate. Used for a model sized by its parameter count; the answer's workload.weights_gb is null when it was not (an image or speech model sized as a whole pipeline).
  • budget_usd_hr · number · optionnel
    Hard limit on the hourly price of the whole configuration, in USD. Configurations above it are not returned.
  • max_total_usd · number · optionnel
    Hard limit on estimated_total_usd, the GPU rental cost of the whole job, in USD. Needs duration_hours. Configurations above it are not returned.
  • duration_hours · number · optionnel
    How long the job will run, in hours (fractions are fine). When sent, each match carries billed_hours and estimated_total_usd.
  • min_gpu_memory_gb · integer · optionnel
    Memory each GPU card must have, in GB (e.g. 80 for 80GB-class cards such as the H100 or A100 80GB). Smaller cards are never returned. On its own it lists every card that size, cheapest first.
  • max_quote_age_minutes · number · optionnel
    Hard limit on how old a price quote may be, in minutes. Configurations whose price was fetched from the provider longer ago are not returned.

  Exemple d'appel

  {"name": "match_workload", "arguments": {"spot": "true", "task": "inference", "model": "texte", "query": "texte", "region": "US", "vram_gb": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"hero": {}, "note": "texte", "as_of": "texte", "count": 1, "error": "texte", "stale": true, "limits": {}, "matches": [], "workload": {}, "updated_at": "texte"}}

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Source

https://fastgpu.co/api/mcp