FastGPU

Compare live GPU cloud rental prices and match workloads to the cheapest provider.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
90%
Qualität der Benennung
90%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,074Tokens (Tool-Definitionen)
~5.2 KBTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (0.84% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "fastgpu": {
      "url": "https://fastgpu.co/api/mcp"
    }
  }
}

Remote-Endpunkte

https://fastgpu.co/api/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (2)

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🟢list_gpu_prices(vendor, tier)

One entry per GPU model with the current cheapest live rental price across the whole market (RunPod, Vast.ai, Lambda, hyperscalers and more). No key required. Use this to compare GPU prices.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "vendor": {
      "type": "string",
      "description": "Filter by GPU vendor.",
      "enum": [
        "NVIDIA",
        "AMD"
      ]
    },
    "tier": {
      "type": "string",
      "description": "Filter by tier.",
      "enum": [
        "flagship",
        "datacenter",
        "prosumer",
        "entry"
      ]
    }
  }
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "updated_at": {
      "type": [
        "string",
        "null"
      ]
    },
    "stale": {
      "type": "boolean"
    },
    "count": {
      "type": "integer"
    },
    "gpus": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "gpu": {
            "type": "string"
          },
          "vram_gb": {
            "type": [
              "number",
              "null"
            ]
          },
          "vendor": {
            "type": [
              "string",
              "null"
            ]
          },
          "arch": {
            "type": [
              "string",
              "null"
            ]
          },
          "tier": {
            "type": [
              "string",
              "null"
            ]
          },
          "cheapest_usd_hr": {
            "type": [
              "number",
              "null"
            ]
          },
          "cheapest_provider": {
            "type": [
              "string",
              "null"
            ]
          },
          "cheapest_min_gpu_count": {
            "type": [
              "integer",
              "null"
            ]
          },
          "provider_count": {
            "type": "integer"
          },
          "offer_count": {
            "type": "integer"
          },
          "url": {
            "type": "string"
          }
        }
      }
    }
  },
  "required": [
    "count",
    "gpus"
  ]
}
🟢match_workload(query, model, params_b, vram_gb, task, ...)

The routing DECISION: describe a job (a model, size, or GPU need) and get the ranked, reasoned recommendation for the cheapest place to run it across the live market, with the required VRAM, GPU count, effective $/hr, and how much cheaper it is than a hyperscaler. No key required. Results mirror the site and apply a small, disclosed partner tie-break between otherwise-equal offers (each match reports partner true/false).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Plain-language job, e.g. \"cheapest to serve Llama 3 70B\" or \"2x H100 for fine-tuning\". Provide this OR a structured spec below."
    },
    "model": {
      "type": "string",
      "description": "Open model name to size against, e.g. \"Llama 3 70B\", \"Qwen 72B\", \"Mixtral\"."
    },
    "params_b": {
      "type": "number",
      "description": "Model size in billions of parameters when no exact model is named."
    },
    "vram_gb": {
      "type": "integer",
      "description": "Rough VRAM the job needs, in GB, if you already know it."
    },
    "task": {
      "type": "string",
      "description": "What the job does.",
      "enum": [
        "inference",
        "finetune-lora",
        "finetune-full",
        "generate",
        "transcribe",
        "embed"
      ]
    },
    "precision": {
      "type": "string",
      "description": "Numeric precision to size the model at.",
      "enum": [
        "fp16",
        "int8",
        "int4"
      ]
    },
    "gpu_count": {
      "type": "integer",
      "description": "Exact positive GPU count. Overrides a count in query text. Returns no matches if no supported configuration fits; omit for automatic sizing."
    },
    "budget_usd_hr": {
      "type": "number",
      "description": "Only recommend configs at or under this hourly budget."
    },
    "region": {
      "type": "string",
      "description": "Restrict to a data-residency region.",
      "enum": [
        "US",
        "EU",
        "ASIA"
      ]
    },
    "spot": {
      "type": "string",
      "description": "Set true to include interruptible spot capacity for a cheaper rate.",
      "enum": [
        "true",
        "false"
      ]
    },
    "reserved": {
      "type": "string",
      "description": "Set true to include reserved / committed-term capacity for a lower rate.",
      "enum": [
        "true",
        "false"
      ]
    }
  }
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "updated_at": {
      "type": [
        "string",
        "null"
      ]
    },
    "stale": {
      "type": "boolean"
    },
    "workload": {
      "type": "object",
      "properties": {
        "interpretation": {
          "type": "string"
        },
        "identified": {
          "type": "boolean"
        },
        "task": {
          "type": "string"
        },
        "precision": {
          "type": "string"
        },
        "vram_required_gb": {
          "type": "number"
        },
        "gpu_count": {
          "type": [
            "integer",
            "null"
          ]
        }
      }
    },
    "hero": {
      "type": [
        "object",
        "null"
      ],
      "properties": {
        "hyperscaler_ceiling": {
          "type": [
            "string",
            "null"
          ]
        },
        "savings_pct": {
          "type": [
            "number",
            "null"
          ]
        },
        "same_model": {
          "type": [
            "boolean",
            "null"
          ]
        }
      }
    },
    "count": {
      "type": "integer"
    },
    "matches": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "gpu": {
            "type": "string"
          },
          "gpu_count": {
            "type": "integer"
          },
          "effective_usd_hr": {
            "type": "number"
          },
          "monthly_usd": {
            "type": "number"
          },
          "provider": {
            "type": "string"
          },
          "provider_label": {
            "type": [
              "string",
              "null"
            ]
          },
          "offer_type": {
            "type": "string"
          },
          "reliability": {
            "type": "string"
          },
          "fits_single_card": {
            "type": "boolean"
          },
          "over_budget": {
            "type": "boolean"
          },
          "tokens_per_sec": {
            "type": [
              "number",
              "null"
            ]
          },
          "usd_per_million_tokens": {
            "type": [
              "number",
              "null"
            ]
          },
          "score": {
            "type": [
              "number",
              "null"
            ]
          },
          "partner": {
            "type": "boolean"
          },
          "reason": {
            "type": "string"
          },
          "url": {
            "type": "string"
          }
        }
      }
    }
  },
  "required": [
    "count",
    "matches"
  ]
}

Empfohlene Prompts

list_items
List all [items] available in FastGPU
Erwartete Tools: list_gpu_prices
browse_collection
Show me the [collection] from FastGPU
Erwartete Tools: list_gpu_prices

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