Local Model Suitability MCP

Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
100%
Qualität der Benennung
100%
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

~530Tokens (Tool-Definitionen)
~4.9 KBTypische Antwortgröße
Minimale Auswirkung auf die Aufmerksamkeit (0.41% 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": {
    "local-model-suitability-mcp": {
      "command": "npx",
      "args": [
        "local-model-suitability-mcp"
      ]
    }
  }
}

Ausführbare Pakete

npmlocal-model-suitability-mcp1.1.23stdio

Remote-Endpunkte

https://local-model-suitability-mcp-production.up.railway.appstreamable-http

Was es kann

Tool-Inventar

Tools (1)

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🟢check_local_viability(task, quality_threshold, data_sensitivity)

Checks whether a task can be handled by a local model instead of a cloud API. Call this BEFORE your agent routes any task to a cloud model — at the moment a task is ready to be sent and the model has not yet been selected. Use this when your agent is about to make a cloud inference call and wants to determine whether a local model could handle it at lower cost. Returns LOCAL/CLOUD/EITHER verdict with recommended model. If verdict is LOCAL, skip the cloud call entirely — saves cost on every routable inference call. Pass data_sensitivity=CONFIDENTIAL to force LOCAL verdict for tasks that must not leave the machine. Do not route to cloud without checking local viability first.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "task": {
      "type": "string",
      "description": "The exact task you are about to send to a cloud model. Be specific — include what the input is and what output you need."
    },
    "quality_threshold": {
      "type": "string",
      "enum": [
        "PRODUCTION",
        "PROTOTYPE",
        "BEST_EFFORT"
      ],
      "description": "PRODUCTION = output quality matters and errors are costly. PROTOTYPE = approximate results acceptable. BEST_EFFORT = speed and cost trump quality. Defaults to PRODUCTION."
    },
    "data_sensitivity": {
      "type": "string",
      "enum": [
        "PUBLIC",
        "INTERNAL",
        "CONFIDENTIAL"
      ],
      "description": "CONFIDENTIAL forces LOCAL verdict regardless of task complexity — data must not leave the machine. Defaults to PUBLIC."
    }
  },
  "required": [
    "task"
  ]
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "verdict": {
      "type": "string",
      "enum": [
        "LOCAL",
        "CLOUD",
        "EITHER"
      ]
    },
    "confidence": {
      "type": "string",
      "enum": [
        "HIGH",
        "MEDIUM",
        "LOW"
      ]
    },
    "reason": {
      "type": "string"
    },
    "estimated_cost_saving": {
      "type": "string"
    },
    "recommended_local_models": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Present when verdict is LOCAL or EITHER"
    },
    "cloud_justified_reason": {
      "type": [
        "string",
        "null"
      ],
      "description": "Non-null only when verdict is CLOUD"
    },
    "data_sensitivity_override": {
      "type": "boolean",
      "description": "Present only when data_sensitivity=CONFIDENTIAL forced a LOCAL verdict"
    },
    "task_quality_threshold": {
      "type": "string",
      "enum": [
        "PRODUCTION",
        "PROTOTYPE",
        "BEST_EFFORT"
      ]
    },
    "data_sensitivity": {
      "type": "string",
      "enum": [
        "PUBLIC",
        "INTERNAL",
        "CONFIDENTIAL"
      ]
    },
    "analysis_type": {
      "type": "string"
    },
    "checked_at": {
      "type": "string",
      "format": "date-time"
    },
    "_disclaimer": {
      "type": "string"
    }
  },
  "required": [
    "verdict",
    "confidence",
    "reason",
    "checked_at",
    "_disclaimer"
  ],
  "additionalProperties": true
}

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