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Pratik-Pou

Scopus MCP Server

by Pratik-Pou
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TypeScript
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation4/5

    The three tools have clearly distinct primary actions: searching versus retrieving by Scopus ID. However, get_article_details and get_article_abstract overlap since details also includes the abstract when available, which could cause minor confusion about which to call.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: search_scopus, get_article_details, get_article_abstract. The get_article_* prefix for the two retrieval tools reinforces a predictable structure.

    Tool Count4/5

    Three tools is on the small side but appropriately scoped for a simple search-and-retrieve workflow. The count feels slightly thin for a general-purpose Scopus API wrapper, but each tool serves a necessary step in the primary flow.

    Completeness4/5

    The core lifecycle of discovering articles and retrieving full metadata or abstracts is covered, with no dead ends. Minor gaps exist, such as no direct citation-list or author-detail endpoints, but these are reasonable omissions given the stated purpose.

  • Average 4.3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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

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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?

    With no annotations provided, the description carries the burden of behavioral disclosure. It usefully documents an important edge case: missing abstracts return hasAbstract:false with a null abstract, common for older or non-English-language records. It does not cover invalid-ID behavior, but for a simple read operation this is a reasonable level of transparency.

    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 two sentences with no filler. The main purpose is front-loaded, and the second sentence adds valuable edge-case behavior without being verbose.

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

    Completeness4/5

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

    For a simple one-parameter tool with no output schema, the description covers the main purpose and a key edge case. It partially describes the return contract via hasAbstract and abstract, though it does not mention invalid-ID behavior. Overall, the core information needed to call the tool correctly is present.

    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?

    The single parameter has full schema coverage with a description and example. The tool description adds no parameter-specific meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

    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 uses a specific verb and resource: 'Retrieve just the abstract text for a single Scopus article by its Scopus ID.' The qualifiers 'just' and 'single' clearly distinguish this from the sibling tools search_scopus and get_article_details.

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

    Usage Guidelines3/5

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

    The description implies when to use this tool: when only the abstract is needed and a Scopus ID is already known. However, it does not explicitly mention alternatives or exclusions, such as using search_scopus to find the ID or get_article_details for full metadata.

    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?

    With no annotations, the description carries the behavioral burden. It describes what the call returns, including the conditional 'abstract (when available),' which clarifies a key edge case. It does not discuss auth, rate limits, or invalid-ID behavior, but the enumerated output is enough for this simple read operation.

    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 one sentence with no filler. The core action and ID source are front-loaded, and the field list is an efficient way to convey the return shape.

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

    Completeness4/5

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

    For a one-parameter lookup with no output schema, the description covers the essential context: what to provide, where to get it, and what metadata will come back. It could add behavior for missing/unknown IDs, but nothing critical is missing for normal invocation.

    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?

    The schema already describes scopusId and the automatic prefix stripping, so the baseline is high. The description adds provenance semantics by telling the agent to use a scopusId returned by search_scopus, which is useful information not present in the schema.

    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 names a specific verb and resource: 'Retrieve full metadata for a single Scopus article by its Scopus ID.' The enumeration of fields (title, authors, DOI, citation count, etc.) makes the purpose concrete and distinct from a search or abstract-only tool.

    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?

    It gives an explicit usage pointer: 'Use the scopusId returned by search_scopus,' which tells the agent where the required ID comes from. It does not explicitly say when to prefer the sibling get_article_abstract over this tool, so it stops short of full exclusion guidance.

    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?

    No annotations are provided, so the description carries the burden of behavioral disclosure. It covers the return payload, count defaults and limits, and the conditional presence of abstracts. It does not mention rate limits, auth requirements, or explicit read-only status, but for a search tool the core behavior is well disclosed.

    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?

    Three sentences with no filler. It front-loads the purpose, then the return contract, then the follow-up workflow—every sentence adds value and is 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?

    Even without an output schema, the description lists the returned fields, count constraints, and a nuanced caveat about abstract availability. The tool has only two simple parameters, and the description gives an agent enough context to invoke it correctly and interpret results.

    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 100%, so the baseline is 3. The description reiterates the query modes and count behavior already present in the schema without adding significant new parameter meaning beyond what the schema provides.

    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 uses a specific verb ('Search'), a clear resource ('Scopus'), and identifies the search facets: author name, keywords, title, or DOI. It also distinguishes itself from siblings by describing candidate-finding versus get_article_details/get_article_abstract metadata retrieval.

    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?

    Explicitly states the intended workflow: 'Use this first to find candidate articles, then call get_article_details or get_article_abstract with a returned scopusId for full metadata.' This tells an agent exactly when to use this tool and how to proceed afterward.

    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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