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andybrandt

mcp-simple-pubmed

by andybrandt
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • 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.

  • Average 4.5/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 2 of 3 community issues answered or closed in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • 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.

  • 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.

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