reviewpaper.ai

Review forms for 29 ML/NLP/CV venues, AI conference deadlines and ICLR acceptance odds.

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도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.

컨텍스트 비용

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~1.1 KB일반적인 응답 크기
중간 정도의 주의 영향 (128k 컨텍스트의 1.07%)

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설치

원클릭 설치

`claude_desktop_config.json` 파일에 다음을 추가하세요:

{
  "mcpServers": {
    "reviewpaper": {
      "url": "https://reviewpaper.ai/mcp"
    }
  }
}

원격 엔드포인트

https://reviewpaper.ai/mcpstreamable-http

할 수 있는 일

도구 목록

도구 (7)

🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢list_venues(area)

List the 29 ML / NLP / CV / data-mining venues whose reviewer forms reviewpaper.ai models, with the overall score scale, whether the form is official or modeled, and links. Use get_review_form for the full form.

입력 스키마

{
  "type": "object",
  "properties": {
    "area": {
      "description": "Optional venue area filter.",
      "type": "string",
      "enum": [
        "ml",
        "cv",
        "nlp",
        "ai",
        "data-mining",
        "ir-web",
        "speech",
        "robotics",
        "theory",
        "systems",
        "multimedia"
      ]
    }
  },
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢get_review_form(venue)

The exact reviewer form for a venue: every field in order with guidance, each score scale with its official labels, the author checklist, the area-chair meta-review, the rough acceptance bar and the venue's LLM policy. Accepts a slug, name or alias (e.g. 'iclr', 'NeurIPS', 'ACL Rolling Review', 'cvpr').

입력 스키마

{
  "type": "object",
  "properties": {
    "venue": {
      "type": "string",
      "minLength": 2,
      "description": "Venue slug, name or alias, e.g. 'iclr' or 'CVPR'."
    }
  },
  "required": [
    "venue"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢list_deadlines(area, within_days, include_estimated, limit)

Upcoming paper and abstract deadlines for ~64 ML, CV, NLP, robotics, speech, data-mining and AI conferences, soonest first, in AoE and ISO-8601 UTC. Projected (not yet announced) dates are excluded unless include_estimated is true.

입력 스키마

{
  "type": "object",
  "properties": {
    "area": {
      "description": "Area code: ML (Machine learning), CV (Computer vision), NLP (Natural language processing), RO (Robotics), SP (Speech and signal processing), DM (Data mining), AP (Applications (health, bio, finance…)), KR (Knowledge representation and planning), HCI (Human-computer interaction), IRSM (Information retrieval and social media), MISC (Other).",
      "type": "string",
      "enum": [
        "ML",
        "CV",
        "NLP",
        "RO",
        "SP",
        "DM",
        "AP",
        "KR",
        "HCI",
        "IRSM",
        "MISC"
      ]
    },
    "within_days": {
      "default": 120,
      "description": "Only deadlines within this many days.",
      "type": "integer",
      "minimum": 1,
      "maximum": 400
    },
    "include_estimated": {
      "default": false,
      "description": "Include dates projected from last year.",
      "type": "boolean"
    },
    "limit": {
      "default": 30,
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    }
  },
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢get_deadline(conference)

Full timeline for one conference edition: abstract/registration, paper, author response and decision dates (AoE + ISO), plus links to its review form. Accepts 'cvpr-2027', 'CVPR 2027' or just 'CVPR' (next upcoming edition).

입력 스키마

{
  "type": "object",
  "properties": {
    "conference": {
      "type": "string",
      "minLength": 2,
      "description": "e.g. 'cvpr-2027', 'ICML 2027', 'neurips'."
    }
  },
  "required": [
    "conference"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢iclr_acceptance_odds(scores, year)

Historical ICLR acceptance rate for papers with similar reviewer ratings, from public OpenReview decisions (kernel estimate over past score profiles). Give 3–6 ratings as the reviewers gave them. Not a prediction of any decision.

입력 스키마

{
  "type": "object",
  "properties": {
    "scores": {
      "minItems": 3,
      "maxItems": 6,
      "type": "array",
      "items": {
        "type": "number",
        "minimum": 0,
        "maximum": 10
      },
      "description": "Reviewer ratings, e.g. [6, 6, 8, 4]."
    },
    "year": {
      "description": "Reference year: 2026, 2025, 2024 (default: latest).",
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991
    }
  },
  "required": [
    "scores"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢convert_score(venue, score, to)

Map an overall review score at one venue to the same position on other venues' scales, keeping its distance from each venue's rough acceptance bar. A heuristic for intuition, not an official equivalence.

입력 스키마

{
  "type": "object",
  "properties": {
    "venue": {
      "type": "string",
      "minLength": 2,
      "description": "Venue the score is from, e.g. 'neurips'."
    },
    "score": {
      "type": "number",
      "description": "Overall score on that venue's scale."
    },
    "to": {
      "description": "Target venues (default: all).",
      "type": "array",
      "items": {
        "type": "string"
      }
    }
  },
  "required": [
    "venue",
    "score"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}
🟢get_llm_policy(venue)

What a venue allows authors and reviewers to do with LLMs, with the official policy link. Use before advising someone on AI use for a submission or a review.

입력 스키마

{
  "type": "object",
  "properties": {
    "venue": {
      "type": "string",
      "minLength": 2,
      "description": "Venue slug, name or alias."
    }
  },
  "required": [
    "venue"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}

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