tomesphere

Search 8.5M scientific papers with LLM TLDRs, citations, linked entities, figures, and full text.

使うべきか

品質と安全性

A
説明の品質
94%
スキーマの完全性
100%
命名の品質
93%
ポイズニングのリスク
100%
権限の一致
100%
プロトコルへの準拠
100%

検出事項(1)

  • LOWTool 'get_structure' description lacks action verbget_structure 内

ツール定義とプロトコルへの準拠に関する自動分析に基づいています。

コンテキストコスト

~1,354トークン数(ツール定義)
~598 B一般的なレスポンスサイズ
注意への影響は中程度(128k コンテキストの 1.06%)

これは、サーバーのツールがモデルのコンテキストに読み込まれるたびに消費されるおおよそのトークン数です。数が多いほど、ほかのタスクに使える注意が減ります。

インストール

ワンクリックインストール

これを `claude_desktop_config.json` ファイルに追加してください:

{
  "mcpServers": {
    "tomesphere": {
      "url": "https://mcp.tomesphere.com/api/mcp"
    }
  }
}

リモートエンドポイント

https://mcp.tomesphere.com/api/mcpstreamable-http

できること

ツール一覧

ツール(9)

🟢 読み取り専用🟡 書き込み🔴 削除⚪ 不明
🟢search_papers(query, k, year_min, year_max)

Search 8.5 million academic papers (arXiv + biomedical: PMC / bioRxiv / medRxiv, all disciplines) by topic, keyword, author, or linked entity (gene / protein / disease). Each hit returns id, title, TLDR, type, and links. Use to find papers about a topic, e.g. 'transformer efficiency' or 'CRISPR base editing'.

入力スキーマ

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Natural-language search query. E.g. 'transformer attention efficiency', 'graph neural networks for molecular property prediction'."
    },
    "k": {
      "type": "integer",
      "description": "Number of results (default 10, max 25).",
      "default": 10
    },
    "year_min": {
      "type": "integer",
      "description": "Earliest publication year, e.g. 2024."
    },
    "year_max": {
      "type": "integer",
      "description": "Latest publication year."
    }
  },
  "required": [
    "query"
  ]
}
🟢get_paper(id)

Fetch a paper's full metadata: title, authors, year, abstract, TLDR (LLM-generated), key findings, citation count, GitHub repos, HuggingFace models/datasets, videos, peer reviews, and links. Accepts an arXiv ID (e.g. '2401.12345' or '1706.03762v5') or an OpenAlex Work ID (e.g. 'W4390723197'). Use when the user names a specific paper or pastes an arXiv link.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID like '2401.12345' or OpenAlex Work ID like 'W4390723197'."
    }
  },
  "required": [
    "id"
  ]
}
🟢similar_papers(id, k)

Find papers semantically similar to a given paper using SPECTER2 embeddings (trained on scientific-citation triplets). Returns nearest neighbors with TLDR. Use when the user wants 'papers like X' or 'what's adjacent to this work'.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID or OpenAlex Work ID."
    },
    "k": {
      "type": "integer",
      "description": "Number of neighbors (default 10, max 25).",
      "default": 10
    }
  },
  "required": [
    "id"
  ]
}
🟢citations(id, k)

Get papers that cite the given paper (who refers to this work). Use when the user asks 'who cites X', 'what's the impact', or wants follow-up work. Note: 2024+ citation coverage is sparse; indexing in progress.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID or OpenAlex Work ID."
    },
    "k": {
      "type": "integer",
      "description": "Max citing papers (default 25, max 100).",
      "default": 25
    }
  },
  "required": [
    "id"
  ]
}
🟢references(id, k)

Get the papers that this paper cites (its bibliography). Use when the user asks 'what does X cite' or 'show me the references'.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID or OpenAlex Work ID."
    },
    "k": {
      "type": "integer",
      "description": "Max references (default 25, max 100).",
      "default": 25
    }
  },
  "required": [
    "id"
  ]
}
🟢get_full_text(id)

Fetch a paper's full body text as Markdown (methods, results, protocols, inline tables) — use for deep questions the abstract can't answer. Accepts an arXiv ID (2401.12345), a PMC ID (PMC5339222), or a bioRxiv/medRxiv DOI (10.1101/…).

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID, PMC ID, or 10.1101/… DOI."
    }
  },
  "required": [
    "id"
  ]
}
🟢get_figures(id)

Get a paper's real figure images — URLs, labels, and captions. Most biomedical papers have figures; arXiv papers often don't. Accepts an arXiv ID, PMC ID, or bioRxiv/medRxiv DOI.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID, PMC ID, or 10.1101/… DOI."
    }
  },
  "required": [
    "id"
  ]
}
🟢get_entities(id)

Get the biomedical entities linked to a paper: genes, proteins, chemicals, diseases, species, mutations, cell lines, and clinical-trial (NCT) IDs. Accepts an arXiv ID, PMC ID, or bioRxiv/medRxiv DOI.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "arXiv ID, PMC ID, or 10.1101/… DOI."
    }
  },
  "required": [
    "id"
  ]
}
🟢get_structure(name)

Resolve a gene/protein name (e.g. 'TP53', 'CD44') or UniProt accession to its 3D structure — returns the UniProt accession + AlphaFold model URL (and PDB when available). Great for a gene named in a paper's entities.

入力スキーマ

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Gene/protein symbol (TP53, CD44) or UniProt accession (P04637)."
    }
  },
  "required": [
    "name"
  ]
}

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最近の観測

検証済みバージョンは記録されていませんツール 9 件
検証済みバージョンは記録されていませんツール 9 件
検証済みバージョンは記録されていませんツール 9 件