Syftly
Ranks the best AI tool or API per task: transcription, TTS, web search, scraping and OCR.
사용해야 할까요
품질 및 안전성
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": {
"syftly": {
"url": "https://syftly.vercel.app/api/mcp"
}
}
}원격 엔드포인트
https://syftly.vercel.app/api/mcpstreamable-http할 수 있는 일
도구 목록
도구 (1)
🟢find_best_tool(query, category)
Given a natural-language question about which AI tool or API is best for a task (currently transcription, text-to-speech, web search, scraping & browser and ocr & document extraction), return Syftly's ranked recommendation: a citeable summary, a provider table with prices and trade-offs, dated sources, and a confidence label. Ask in plain English about price, accuracy, language or capability trade-offs — e.g. 'best OCR API for scanned PDFs' or 'best web scraping API for JavaScript-heavy sites'. Optionally pass "category" to disambiguate; otherwise it is detected from the question.
입력 스키마
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The question in natural language, e.g. 'best transcription API for Dutch'."
},
"category": {
"type": "string",
"description": "Optional category id to disambiguate the question; omit to let Syftly detect it.",
"enum": [
"transcription",
"tts",
"web-search",
"scraping",
"ocr"
]
}
},
"required": [
"query"
],
"additionalProperties": false
}출력 스키마
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The human question (page H1)."
},
"slug": {
"type": "string"
},
"category": {
"type": "string",
"description": "e.g. 'transcription'; '' on a no-match."
},
"routing": {
"type": "string",
"enum": [
"matched",
"none",
"ambiguous"
],
"description": "Honest routing outcome: 'matched' = answered from a real category; 'none' = no category matched (out-of-scope/gibberish) — an honest no-match, not a fabricated answer; 'ambiguous' = fit 2+ categories. 'none'/'ambiguous' carry `categories` and no real recommendation/providers."
},
"summary": {
"type": "string",
"description": "Citeable summary, 40-80 words, reused verbatim across all views. On a no-match, the plain-language message."
},
"confidence": {
"type": "string",
"enum": [
"light estimate",
"hard tested"
],
"description": "Confidence/depth label."
},
"updated": {
"type": "string",
"description": "ISO date."
},
"recommendation": {
"type": "object",
"required": [
"default",
"axes"
],
"properties": {
"default": {
"type": "string",
"description": "Name of the recommended offering ('' on a no-match)."
},
"axes": {
"type": "object",
"description": "Decision-axis -> recommended offering. Carries EVERY matched axis: filters + all ordering axes, each naming its own computed winner.",
"additionalProperties": {
"type": "string"
}
},
"primary": {
"type": "string",
"description": "The axis key whose winner became `default` when 2+ ordering axes conflict with no composite tiebreak — the earliest-in-query axis. Absent for single-axis/composite-resolved answers."
}
}
},
"providers": {
"type": "array",
"items": {
"type": "object",
"required": [
"name",
"provider",
"price",
"metrics",
"strengths",
"weaknesses",
"source",
"source_date"
],
"properties": {
"name": {
"type": "string",
"description": "The callable offering, e.g. 'Deepgram Nova-3'."
},
"provider": {
"type": "string",
"description": "The company behind it, e.g. 'Deepgram'."
},
"model_family": {
"type": "string",
"description": "Filter attribute, not a row of its own."
},
"price": {
"type": "object",
"required": [
"value",
"unit"
],
"properties": {
"value": {
"type": [
"number",
"null"
]
},
"unit": {
"type": "string",
"description": "e.g. '$/min', '$/1000min'."
},
"comparable": {
"type": "boolean",
"description": "false = token-/credit-priced, not directly comparable (excluded from the price axis)."
}
}
},
"metrics": {
"type": "object",
"description": "Open category-specific decision-axis fields. Keys are stable data identifiers (e.g. 'wer', 'latency_ms'); values are number, boolean, string or null (null = an honest gap). Number metrics back min/max axes; boolean metrics back filter axes.",
"additionalProperties": {
"type": [
"number",
"boolean",
"string",
"null"
]
}
},
"strengths": {
"type": "string"
},
"weaknesses": {
"type": "string"
},
"source": {
"type": "string",
"description": "Where this row's facts come from."
},
"source_date": {
"type": "string",
"description": "ISO date of the source."
}
}
}
},
"sources": {
"type": "array",
"items": {
"type": "object",
"required": [
"title",
"url",
"date"
],
"properties": {
"title": {
"type": "string"
},
"url": {
"type": "string",
"format": "uri"
},
"date": {
"type": "string",
"description": "ISO date."
}
}
}
},
"categories": {
"type": "array",
"description": "Present only when routing !== 'matched': the supported categories so the caller can re-ask in scope.",
"items": {
"type": "object",
"required": [
"category",
"label"
],
"properties": {
"category": {
"type": "string",
"description": "Supported category id, e.g. 'web-search'."
},
"label": {
"type": "string",
"description": "Human label, e.g. 'Web search'."
}
}
}
}
},
"required": [
"query",
"slug",
"category",
"routing",
"summary",
"confidence",
"updated",
"recommendation",
"providers",
"sources"
],
"additionalProperties": false
}커뮤니티
증거