tomesphere
Search 8.5M scientific papers with LLM TLDRs, citations, linked entities, figures, and full text.
사용해야 할까요
품질 및 안전성
발견 사항 (1)
- LOWTool 'get_structure' description lacks action verbget_structure에서
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": {
"tomesphere": {
"url": "https://mcp.tomesphere.com/api/mcp"
}
}
}원격 엔드포인트
https://mcp.tomesphere.com/api/mcpstreamable-http할 수 있는 일
도구 목록
도구 (9)
🟢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'.
입력 스키마
{
"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.
입력 스키마
{
"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'.
입력 스키마
{
"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.
입력 스키마
{
"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'.
입력 스키마
{
"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/…).
입력 스키마
{
"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.
입력 스키마
{
"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.
입력 스키마
{
"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.
입력 스키마
{
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Gene/protein symbol (TP53, CD44) or UniProt accession (P04637)."
}
},
"required": [
"name"
]
}커뮤니티
증거