AgentKernel AI model data
Live prices, rankings, licences and privacy of AI models: best model per task, costs, alternatives.
사용해야 할까요
품질 및 안전성
발견 사항 (1)
- LOWTool 'estimate_cost' description lacks action verbestimate_cost에서
도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.
컨텍스트 비용
이는 서버의 도구가 모델의 컨텍스트에 로드될 때마다 소비되는 대략적인 토큰 수입니다. 수치가 높을수록 다른 작업에 사용할 수 있는 주의가 줄어듭니다.
설치
원클릭 설치
`claude_desktop_config.json` 파일에 다음을 추가하세요:
{
"mcpServers": {
"models": {
"url": "https://www.agentkernel.si/mcp"
}
}
}원격 엔드포인트
https://www.agentkernel.si/mcpstreamable-http할 수 있는 일
도구 목록
도구 (6)
🟢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.
입력 스키마
{
"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.
입력 스키마
{
"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.
입력 스키마
{
"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.
입력 스키마
{
"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.
입력 스키마
{
"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.
입력 스키마
{
"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
}커뮤니티
증거