AgentKernel AI model data

Live prices, rankings, licences and privacy of AI models: best model per task, costs, alternatives.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
95%
Vollständigkeit des Schemas
83%
Qualität der Benennung
87%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (1)

  • LOWTool 'estimate_cost' description lacks action verbin estimate_cost

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

Kontextkosten

~1,095Tokens (Tool-Definitionen)
~1.4 KBTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (0.86% 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": {
    "models": {
      "url": "https://www.agentkernel.si/mcp"
    }
  }
}

Remote-Endpunkte

https://www.agentkernel.si/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (6)

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🟢best_for_task(task, license, limit)

Ranks AI models for one task by performance only (price shown, never used for the rank). Tasks cover text, coding, agents, websites/UI/games/data viz, image generation and editing, video from text or image, video editing, text to speech, transcription, music and embeddings.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "task": {
      "type": "string",
      "enum": [
        "overall",
        "coding",
        "agents",
        "websites",
        "ui-components",
        "game-development",
        "data-visualization",
        "3d-scenes",
        "svg-graphics",
        "web-apps",
        "full-stack",
        "mobile-apps",
        "image-generation",
        "image-editing",
        "graphics-and-logos",
        "text-to-video",
        "image-to-video",
        "video-editing",
        "text-to-speech",
        "transcription",
        "music",
        "embeddings"
      ],
      "description": "Task slug"
    },
    "license": {
      "type": "string",
      "enum": [
        "all",
        "open",
        "closed"
      ],
      "default": "all",
      "description": "open = open weights only, closed = proprietary only"
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 25,
      "default": 10
    }
  },
  "required": [
    "task"
  ],
  "additionalProperties": false
}
🟢recommend_models(use_case, monthly_budget_usd, priority, input_tokens, output_tokens, ...)

Returns the best-fitting language models for a use case and monthly API budget using the published AgentKernel Fit Score (performance, cost, context, features), with optional privacy and licence requirements.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "use_case": {
      "type": "string",
      "enum": [
        "everyday",
        "coding",
        "agents",
        "documents"
      ]
    },
    "monthly_budget_usd": {
      "type": "number",
      "minimum": 0,
      "default": 10
    },
    "priority": {
      "type": "string",
      "enum": [
        "balanced",
        "quality",
        "saving"
      ],
      "default": "balanced"
    },
    "input_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 1000000,
      "description": "Input tokens per month"
    },
    "output_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 250000,
      "description": "Output tokens per month"
    },
    "privacy": {
      "type": "string",
      "enum": [
        "any",
        "zdr",
        "eu"
      ],
      "default": "any",
      "description": "zdr = zero data retention, eu = zero retention in an EU region"
    },
    "open_weights_only": {
      "type": "boolean",
      "default": false
    },
    "needs_vision": {
      "type": "boolean",
      "default": false
    },
    "include_free": {
      "type": "boolean",
      "default": false
    }
  },
  "required": [
    "use_case"
  ],
  "additionalProperties": false
}
🟢get_model(model, input_tokens, output_tokens)

Price, context window, performance/coding/agentic index with rank, licence, privacy, cost for a usage volume and cheaper or open alternatives for one language model.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "model": {
      "type": "string",
      "description": "Model id like \"anthropic/claude-opus-5.5\" or a name like \"Claude Opus 5.5\""
    },
    "input_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 1000000
    },
    "output_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 250000
    }
  },
  "required": [
    "model"
  ],
  "additionalProperties": false
}
🟢find_models(query, license, privacy, sort, limit)

Searches and filters the catalog of language models by name, provider, licence and privacy, sorted by performance, coding, agentic index, price or context.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Part of a name, id or provider"
    },
    "license": {
      "type": "string",
      "enum": [
        "all",
        "open",
        "closed"
      ],
      "default": "all"
    },
    "privacy": {
      "type": "string",
      "enum": [
        "any",
        "zdr",
        "eu"
      ],
      "default": "any"
    },
    "sort": {
      "type": "string",
      "enum": [
        "performance",
        "coding",
        "agentic",
        "price",
        "context"
      ],
      "default": "performance"
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 25,
      "default": 10
    }
  },
  "additionalProperties": false
}
🟢estimate_cost(models, input_tokens, output_tokens)

Monthly API cost at base rates for up to five models and a token volume, with the volume translated into words and pages.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "models": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "minItems": 1,
      "maxItems": 5
    },
    "input_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 1000000
    },
    "output_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 250000
    }
  },
  "required": [
    "models"
  ],
  "additionalProperties": false
}
🟢cheaper_alternative(model, input_tokens, output_tokens)

For a model you use today, finds a cheaper model at most five performance-index points lower for the same usage.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "model": {
      "type": "string"
    },
    "input_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 1000000
    },
    "output_tokens": {
      "type": "integer",
      "minimum": 0,
      "default": 250000
    }
  },
  "required": [
    "model"
  ],
  "additionalProperties": false
}

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