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mcp-simple-pubmed

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Python
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MCP 심플 퍼브메드

대장간 배지

Entrez API를 통해 PubMed 기사에 대한 액세스를 제공하는 MCP 서버입니다.

특징

  • 키워드를 사용하여 PubMed 데이터베이스 검색

  • 기사 초록에 접근하세요

  • PubMed에서 직접 제공되는 오픈 액세스 기사의 경우 전체 텍스트를 다운로드할 수 있습니다.

이 도구는 전체 텍스트의 XML화된 버전을 반환합니다. 하지만 AI에게는 문서 구조에 대한 추가 정보를 제공하기 때문에 "사람이 읽을 수 있는" 텍스트보다 더 유용합니다. 적어도 클로드 3.5 소넷은 이 부분을 선호한다고 밝혔습니다.

이 도구를 비롯한 다른 도구들이 논문 전문을 제공하지 못하는 것은 해당 도구를 사용할 수 없기 때문만은 아닐 수 있습니다. 이 도구를 테스트하던 중 PubMed에 전문이 없는 논문을 발견했습니다. Claude가 fetch를 사용하여 출판 URL(DOI를 통해 확인했습니다)에 접근했을 때 "금지됨" 오류가 발생했습니다. 하지만 일반 브라우저에서는 동일한 페이지에 접근할 수 있었습니다.

다시 말해, AI 비서가 이 도구를 사용하여 논문의 전문을 얻을 수 없다면 일반 웹 브라우저로 수동으로 시도하는 것이 좋습니다.

마지막으로, 이 도구를 사용해도 유료 논문에 접근할 수는 없습니다. 도서관 접속을 통해 읽을 수 있거나, 최후의 수단으로 공적 자금으로 지원되는 연구를 무료로 이용할 수 있도록 하는 특정 사이트를 통해 읽을 수는 있습니다.

Related MCP server: mcp-pubmed

설치

Smithery를 통해 설치

Smithery를 통해 Claude Desktop에 Simple PubMed를 자동으로 설치하려면:

지엑스피1

수동 설치

pip install mcp-simple-pubmed

구성

서버에는 다음과 같은 환경 변수가 필요합니다.

  • PUBMED_EMAIL : 귀하의 이메일 주소(NCBI에서 필요)

  • PUBMED_API_KEY : 더 높은 속도 제한을 위한 선택적 API 키

표준 속도 제한은 초당 3회 요청입니다. 일반적인 사용 시나리오에서는 AI가 더 많은 트래픽을 생성할 가능성이 매우 낮기 때문에 속도 제한은 구현되지 않았습니다. 필요한 경우 초당 10회 요청을 제공하는 API 키를 등록 할 수 있습니다. NCBI 페이지에서 이에 대한 자세한 내용을 확인하세요.

Claude Desktop과 함께 사용

Claude Desktop 구성( claude_desktop_config.json )에 다음을 추가합니다.

(맥 OS)

{
  "mcpServers": {
    "simple-pubmed": {
      "command": "python",
      "args": ["-m", "mcp_simple_pubmed"],
      "env": {
        "PUBMED_EMAIL": "your-email@example.com",
        "PUBMED_API_KEY": "your-api-key" 
      }
    }
  }
}

(윈도우)

{
  "mcpServers": {
    "simple-pubmed": {
      "command": "C:\\Users\\YOUR_USERNAME\\AppData\\Local\\Programs\\Python\\Python311\\python.exe",
      "args": [
        "-m",
        "mcp_simple_pubmed"
      ],
      "env": {
        "PUBMED_EMAIL": "your-email@example.com",
        "PUBMED_API_KEY": "your-api-key" 
      }
    }
  }
}

특허

MIT 라이센스

Available Tools

2 tools
get_paper_fulltextGet a paper's full textA
Read-only

Get full text of a PubMed article using its ID.

This tool attempts to retrieve the complete text of the paper if available through PubMed Central. If the paper is not available in PMC, it will return a message explaining why and provide information about where the text might be available (e.g., through DOI).

Example usage: get_paper_fulltext(pmid="39661433")

Returns:

  • If successful: The complete text of the paper

  • If not available: A clear message explaining why (e.g., "not in PMC", "requires journal access")

ParametersJSON Schema
NameRequiredDescriptionDefault
pmidYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true and openWorldHint=true, but the description adds valuable behavioral context: it explains that retrieval depends on availability in PubMed Central, describes fallback behavior (returning messages with explanations), and mentions alternative sources like DOI. This enhances transparency beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by behavioral details and example usage. Every sentence adds value without redundancy, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (fetching full text with fallbacks), the description is complete: it covers purpose, usage, behavior, and output scenarios. With an output schema present, it appropriately omits detailed return value explanations, focusing on high-level outcomes like success/failure messages.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates by explaining that the 'pmid' parameter is used to identify the PubMed article. However, it does not provide additional details like format constraints or examples beyond the basic usage. With one parameter and no schema descriptions, the baseline is met but not exceeded.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('retrieve the complete text') and resource ('PubMed article using its ID'), distinguishing it from the sibling tool 'search_pubmed' which likely searches rather than fetches full text. It explicitly mentions PubMed Central as the source, adding specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use this tool (to get full text of a PubMed article by ID) and implies when not to use it (if you need to search, use 'search_pubmed'). However, it does not explicitly name the alternative or detail exclusions, such as handling non-PubMed IDs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_pubmedSearch articles about medical and life sciences research available on PubMed.A
Read-only

Search PubMed for medical and life sciences research articles.

You can use these search features:

  • Simple keyword search: "covid vaccine"

  • Field-specific search:

    • Title search: [Title]

    • Author search: [Author]

    • MeSH terms: [MeSH Terms]

    • Journal: [Journal]

  • Date ranges: Add year or date range like "2020:2024[Date - Publication]"

  • Combine terms with AND, OR, NOT

  • Use quotation marks for exact phrases

Examples:

  • "covid vaccine" - basic search

  • "breast cancer"[Title] AND "2023"[Date - Publication]

  • "Smith J"[Author] AND "diabetes"

  • "RNA"[MeSH Terms] AND "therapy"

The search will return:

  • Paper titles

  • Authors

  • Publication details

  • Abstract preview (when available)

  • Links to full text (when available)

  • DOI when available

  • Keywords and MeSH terms

Note: Use quotes around multi-word terms for best results.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint=true and openWorldHint=true, which the description aligns with by describing a search operation. The description adds valuable behavioral context beyond annotations, such as available search features, return format details (e.g., paper titles, authors, abstract preview), and performance tips, though it doesn't mention rate limits or authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by bullet points and examples that efficiently convey usage without unnecessary details. Every sentence adds value, making it concise and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (search with multiple features), low schema coverage (0%), and presence of an output schema, the description is complete enough. It thoroughly explains search capabilities, return values, and usage, compensating for the lack of schema descriptions and leveraging the output schema for return format details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description compensates well by explaining the 'query' parameter through search features and examples, and it implies the 'max_results' parameter by mentioning return details. However, it doesn't explicitly define 'max_results' or its default value, leaving some gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Search PubMed for medical and life sciences research articles.' This specifies the verb ('Search'), resource ('PubMed'), and domain ('medical and life sciences research articles'), distinguishing it from the sibling tool 'get_paper_fulltext' which presumably retrieves full text rather than searching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool by detailing search features and examples, and it implicitly distinguishes from the sibling tool 'get_paper_fulltext' by focusing on search functionality rather than full-text retrieval. It also includes a note on best practices ('Use quotes around multi-word terms for best results').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv1.0.0
    • First observedget_paper_fulltext
    • First observedsearch_pubmed
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: get_paper_fulltext retrieves the full text of a specific article by ID, while search_pubmed performs keyword-based searches across the PubMed database. There is no overlap or ambiguity between these functions.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern: get_paper_fulltext and search_pubmed. The naming is clear and predictable, with no deviations in style or convention.

Tool Count3/5

With only two tools, the server feels thin for a PubMed interface, as it lacks operations like fetching paper metadata, filtering search results, or managing citations. While the tools cover basic retrieval and search, more comprehensive coverage would typically require additional tools.

Completeness2/5

The tool set is significantly incomplete for a PubMed domain. It lacks essential operations such as get_paper_metadata (for details like authors, journal, abstract without full text), filter_search_results, or citation-related tools. This will likely cause agent failures when trying to perform common PubMed tasks beyond simple search and full-text retrieval.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

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