Agent Data Tools: AI

15 tools: LLM chat, summaries, translation, embeddings, speech, images. From $0.002.

사용해야 할까요

품질 및 안전성

A
설명 품질
100%
스키마 완전성
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이름 품질
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오염 위험
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권한 일치
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프로토콜 준수
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발견 사항 (2)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool description contains URL to non-standard domaintranscribe에서

도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.

컨텍스트 비용

~3,642토큰 (도구 정의)
~976 B일반적인 응답 크기
상당한 주의 영향 (128k 컨텍스트의 2.85%)

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": {
    "agent-data-tools-ai": {
      "url": "https://agent-data-tools.revmesh2074.workers.dev/mcp/ai"
    }
  }
}

원격 엔드포인트

https://agent-data-tools.revmesh2074.workers.dev/mcp/aistreamable-http

할 수 있는 일

도구 목록

도구 (15)

🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢image(prompt, steps)

Text-to-image generation with FLUX.1 schnell. Send a prompt, get a 1024x1024 JPEG back as base64 in a few seconds. Use for illustrations, thumbnails, mockups, avatars and social media images. Optional steps parameter (1-8, default 4) trades speed for detail. Example: prompt=a lighthouse on a cliff at sunset, watercolor. Price $0.02/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string",
      "description": "What the image should show (3-800 characters)"
    },
    "steps": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991,
      "description": "Diffusion steps, 1-8 (default 4)"
    }
  },
  "required": [
    "prompt"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢transcribe(url)

Transcribe speech from an audio file at a public URL using Whisper large-v3-turbo. Returns the transcript text, detected language, duration and word count. Accepts common formats such as MP3, WAV, M4A and OGG up to 5 MB. Use for voice notes, podcast clips, meeting snippets and voice messages. Example: url=https://commons.wikimedia.org/wiki/Special:FilePath/En-us-hello.ogg. Price $0.02/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "description": "Absolute http(s) URL of an audio file (max 5 MB)"
    }
  },
  "required": [
    "url"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢describe(url, question)

Vision model for an image at a public URL: get a detailed description including any visible text, or pass a question to ask something specific about the image. Accepts PNG, JPEG, WebP and GIF up to 3 MB. Use for alt text, OCR-style reading of screenshots, chart reading and content checks. Price $0.01/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "description": "Absolute http(s) URL of a PNG, JPEG, WebP or GIF image (max 3 MB)"
    },
    "question": {
      "type": "string",
      "description": "Optional question about the image (max 300 characters); default is a detailed description"
    }
  },
  "required": [
    "url"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_chat(prompt, system, maxTokens, temperature)

Send a prompt, get an answer from Llama 3.1 8B Instruct, with an optional system prompt, up to 1,024 output tokens and adjustable temperature. Use for drafting, reasoning steps, Q&A and any quick LLM call without an AI provider account. For harder reasoning use ai_chat_large. Example: prompt=Explain x402 in one sentence.. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string",
      "description": "User prompt, up to 8,000 characters"
    },
    "system": {
      "type": "string",
      "description": "Optional system prompt, up to 2,000 characters"
    },
    "maxTokens": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991,
      "description": "Maximum output tokens, 1-1024 (default 400)"
    },
    "temperature": {
      "type": "number",
      "description": "0-1.5 (default 0.6)"
    }
  },
  "required": [
    "prompt"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_chat_large(prompt, model, system, maxTokens, temperature)

Send a prompt, get an answer from a larger open model: Llama 3.3 70B Instruct (default) or OpenAI gpt-oss-120b, with an optional system prompt, up to 1,024 output tokens and adjustable temperature. Same call as /ai/chat with a stronger model. Use when the 8B model is not enough: reasoning, drafting and Q&A. Example: prompt=Explain x402 in one sentence.. Price $0.01/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string",
      "description": "User prompt, up to 8,000 characters"
    },
    "model": {
      "type": "string",
      "enum": [
        "llama-3.3-70b",
        "gpt-oss-120b"
      ],
      "description": "llama-3.3-70b (default) or gpt-oss-120b"
    },
    "system": {
      "type": "string",
      "description": "Optional system prompt, up to 2,000 characters"
    },
    "maxTokens": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991,
      "description": "Maximum output tokens, 1-1024 (default 400)"
    },
    "temperature": {
      "type": "number",
      "description": "0-1.5 (default 0.6)"
    }
  },
  "required": [
    "prompt"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_summarize_text(text, sentences)

Summarize up to 12,000 characters of text you send into a few sentences plus bullet key points. Use for long emails, documents, transcripts and tool outputs (for a web page by URL, use /summarize). Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text to summarize, up to 12,000 characters"
    },
    "sentences": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991,
      "description": "Summary length in sentences, 1-8 (default 3)"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_sentiment(text)

Positive or negative sentiment of English text with a confidence score, from a DistilBERT model fine-tuned on SST-2. Use to triage reviews, support messages, social posts and replies. Example: text=The checkout was fast and support answered within minutes.. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "English text, up to 4,000 characters"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_classify(text, labels)

Zero-shot classification: give text and 2-20 candidate labels, get the best label, a short reason and a ranking. Use for routing tickets, tagging content, intent detection and moderation queues. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text to classify, up to 8,000 characters"
    },
    "labels": {
      "type": "string",
      "description": "Comma-separated candidate labels (2-20)"
    }
  },
  "required": [
    "text",
    "labels"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_keywords(text, count)

The most important keywords and key phrases of a text, most relevant first. Use for tagging, SEO, search indexing and topic detection. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text, up to 12,000 characters"
    },
    "count": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991,
      "description": "How many, 3-30 (default 10)"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_rewrite(text, style)

Rewrite text to be more formal, casual, simpler, shorter, friendlier, more professional or more persuasive, keeping the meaning and language. Use to polish emails, replies, product copy and messages. Example: text=hey, cant make it tmrw, can we move to thu?. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text, up to 8,000 characters"
    },
    "style": {
      "type": "string",
      "enum": [
        "formal",
        "casual",
        "simpler",
        "shorter",
        "friendly",
        "professional",
        "persuasive"
      ],
      "description": "formal, casual, simpler, shorter, friendly, professional or persuasive (default professional)"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_outline(text, depth)

A structured Markdown outline (headings and bullet points) of a text you send, or a suggested outline for a topic. Use to plan articles, reports, talks and documentation. Example: text=How small businesses can accept stablecoin payments. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text to outline, or a topic, up to 12,000 characters"
    },
    "depth": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991,
      "description": "Heading levels, 1-3 (default 2)"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_translate(text, to, from)

Translate text between about 100 languages with Meta's M2M100 1.2B model. Give the target language as an ISO code such as en, sv, de, fr, es, zh or ja; the source language is optional. Use to localise messages and documents. Example: text=Payment received, thank you!, to=sv. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text, up to 4,000 characters"
    },
    "to": {
      "type": "string",
      "description": "Target language code, e.g. sv"
    },
    "from": {
      "type": "string",
      "description": "Source language code (default en)"
    }
  },
  "required": [
    "text",
    "to"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_embed(text)

A 1,024-dimension embedding vector for up to 4,000 characters of text in 100+ languages, from BAAI's BGE-M3. Use for semantic search, RAG retrieval, clustering and deduplication. Example: text=pay-per-call APIs for AI agents. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text to embed, up to 4,000 characters"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_extract_json(text, fields)

Pull named fields out of unstructured text (emails, invoices, listings, bios) and get them back as a JSON object, with null for anything not present. Use to turn messy text into structured data for an agent. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Source text, up to 12,000 characters"
    },
    "fields": {
      "type": "string",
      "description": "Comma-separated field names to extract (1-30)"
    }
  },
  "required": [
    "text",
    "fields"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢ai_speech(text, lang)

Turn up to 1,000 characters of text into natural speech as an audio file (base64, with its content type), in English, Spanish, French, Chinese, Japanese or Korean, with MeloTTS. Use for voice replies, audio notes, accessibility and phone or chat bots. Example: text=Your payment was received. Thank you!. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "description": "Text to speak, up to 1,000 characters"
    },
    "lang": {
      "type": "string",
      "enum": [
        "en",
        "es",
        "fr",
        "zh",
        "ja",
        "ko"
      ],
      "description": "Language: en, es, fr, zh, ja or ko (default en)"
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

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