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ckgerteis

cinii-mcp

by ckgerteis

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v3.0.1

  • Disambiguation5/5

    Each search tool explicitly targets a distinct content type (articles, books, dissertations, KAKEN projects, researchers, and a cross-type search), with no overlap in purpose. The get_record tool is clearly separate as a single-record fetcher by URL or CRID.

    Naming Consistency5/5

    All tools follow the identical pattern 'cinii_search_<type>' for searches, plus 'cinii_get_record' for retrieval, maintaining consistent snake_case and verb-noun ordering throughout.

    Tool Count5/5

    Seven tools is well-scoped for a literature search MCP server, covering the major CiNii content types without redundancy or unnecessary bloat. Each tool earns its place.

    Completeness5/5

    The surface covers all primary search categories (articles, books, dissertations, KAKEN, researchers) plus an all-search and a record fetch, leaving no obvious gaps for the stated purpose of querying CiNii Research.

  • Average 3.5/5 across 7 of 7 tools scored. Lowest: 2.4/5.

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

    • No community issues in the last 6 months
    • 31 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior2/5

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

    Annotations already provide safety information (readOnlyHint=true, idempotentHint=true, destructiveHint=false). The description adds only the phrase 'Returns the unified envelope', which hints at the output format but is redundant given the output schema exists. It does not add behavioral context such as pagination limits, potential delays, or any special handling. Since annotations are present, the bar is lower, but the description still contributes almost nothing beyond the schema.

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

    Conciseness3/5

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

    The description is a single, compact sentence that is easy to read. It is appropriately sized for a simple search tool, but it is overly sparse — it does not elaborate on scope or usage. It is concise without being informative, so it earns a middle score.

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

    Completeness2/5

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

    Given the tool has a rich schema with 10 parameters and is part of a family of similar search tools, the description is insufficient. It does not mention which parameters to use for common scenarios, does not clarify the 'unified envelope' output structure beyond the schema, and omits any guidance on how this tool differs from its siblings. The presence of an output schema covers return format but not usage context.

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

    Parameters2/5

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

    Schema description coverage is 0% — the description does not explain any of the parameters (query, isbn, title, author, etc.). While some parameter names are self-explanatory, the description offers no guidance on how they interact or which are mutually exclusive. With low coverage, the description must compensate, but it does not, leaving the agent to rely on the schema alone.

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

    Purpose4/5

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

    The description states a specific verb ('Search') and a clear resource ('CiNii Research for books and monographs'). It implicitly differentiates from sibling search tools by specifying 'books and monographs', which is distinct from articles, dissertations, and researchers. However, it does not explicitly name a sibling or contrast them, so a 4 is appropriate rather than a 5.

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

    Usage Guidelines1/5

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

    There is no guidance on when to use this tool versus alternatives. The description does not mention that this is the tool for book/monograph searches or that other tools are for different document types. No prerequisites, exclusions, or alternative tools are referenced, leaving the agent to infer usage solely from the name.

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

  • Behavior2/5

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

    Annotations already convey readOnly, openWorld, idempotent, and non-destructive behavior, so the description need not repeat those. However, the only additional behavioral information, 'Returns the unified envelope,' is cryptic and unexplained, leaving the agent unsure about the actual output structure. This adds little transparent value.

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

    Conciseness3/5

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

    The description is very short (a single sentence), so it is concise in word count, but that brevity comes at the cost of essential detail. It lacks any structure (e.g., bullets, sections) to organize information, and the sentence itself is too terse to be complete.

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

    Completeness1/5

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

    Despite having an output schema and a 7-field nested input schema, the description provides almost no context. It does not explain how to form queries, what the 'unified envelope' contains, or how filters work. An agent cannot confidently call this tool without additional documentation, making it severely inadequate for the tool's complexity.

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

    Parameters1/5

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

    Schema description coverage is 0%, so the description has the full burden of explaining parameters. It mentions none of the seven parameters (lang, count, query, start, author, to_year, from_year) nor their meaning. The agent must rely solely on field titles and defaults, which is insufficient for correct invocation.

    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 action ('Search'), the resource ('CiNii Research'), and the specific scope ('doctoral dissertations'). It inherently distinguishes itself from sibling tools that target articles, books, researchers, etc., through the explicit mention of dissertations.

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

    Usage Guidelines2/5

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

    No guidance is given on when to use this tool versus the alternative search tools (e.g., cinii_search_all, cinii_search_articles). The use case is only implied by the tool name and scope, with no explicit 'use this when' or 'for other content types use...' instruction.

    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 already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds a useful, non-obvious note about field mapping (name in title, profile URL in ids.url_ja) that goes beyond the schema. No contradictions; the note clarifies result interpretation without repeating annotation information.

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

    Conciseness4/5

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

    The description is a single concise sentence followed by a clearly separated note. The main purpose is front-loaded, and the note is relevant without bloating the text. Efficient and well-structured.

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

    Completeness2/5

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

    Given the schema has no parameter descriptions and the tool has multiple parameters (query, institution, pagination controls), the description is incomplete. The field-mapping note is helpful, but it doesn't cover parameter semantics or usage context. An agent would need to infer most functional details from parameter names alone.

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

    Parameters1/5

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

    Schema description coverage is 0%, and the description mentions none of the parameters (query, lang, count, start, institution). The tool requires more than one parameter in practice (via the nested 'params' object), yet the description provides no semantic help, leaving the agent to guess from names alone.

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

    Purpose4/5

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

    The description clearly states 'Search for researchers in CiNii' with a specific verb and resource, and mentions the record_type 'researcher'. It differentiates from siblings like cinii_search_articles by resource type, though it doesn't explicitly name alternatives. The purpose is unambiguous.

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

    Usage Guidelines2/5

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

    No guidance is provided on when to use this tool versus cinii_search_all or other sibling search tools. There is no mention of scenarios, prerequisites, or exclusions, leaving the agent to infer usage context from the name alone.

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

  • Behavior3/5

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

    Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and side-effect expectations. The description adds that it returns the unified envelope with record_type 'project', which is a useful behavioral detail. However, it doesn't disclose pagination behavior, result ordering, or potential rate limits. With annotations covering the main traits, the added value is modest but non-trivial.

    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 a single, front-loaded sentence with no filler. It communicates the core purpose and the key return-type detail efficiently, which is ideal for an AI agent that needs to quickly parse tool intent.

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

    Completeness2/5

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

    Given the tool has multiple optional parameters and 0% schema coverage, the description is under-specified. It doesn't explain how to construct a valid query, how filters interact, or any constraints. An output schema exists but is not visible in the prompt; the description only hints at the return envelope. An agent would likely need to inspect the schema or make trial calls to use the tool effectively.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate for the meaning of parameters like query, lang, count, start, from_year, to_year, researcher, and institution. The description only mentions the search action and return type, providing no explanation of how to use the filters. Field names are self-explanatory to some degree, but without any description guidance, an agent may not know parameter formats or combinations.

    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 states a specific verb ('Search') and a clear resource ('KAKEN research projects'), and it distinguishes itself from sibling search tools by specifying the record_type 'project' in the unified envelope. This makes the tool's purpose unambiguous even without reading the schema.

    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 usage for KAKEN projects but does not explicitly contrast with alternatives such as cinii_search_articles or cinii_search_all. There is no 'use this when' or 'not for' guidance. The sibling list is provided in context but the description itself doesn't reference it, so an agent must infer when to choose this tool.

    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 already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, covering the safety profile. The description adds value by stating the return envelope format (operation 'get_record'), which is not in annotations. No contradiction; it contextually enriches what the tool returns.

    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?

    Two crisp sentences: the first states the action and input, the second the expected output. Front-loaded with the core purpose and no filler. Every word earns its place.

    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 single-record fetch with a straightforward input and an output schema provided, the description covers the essential behavior. It mentions the envelope and the operation. The only omission is potential error handling or edge cases, but given the output schema and annotations, it is sufficiently complete for an agent to use correctly.

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

    Parameters2/5

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

    Schema description coverage is 0% because the tool description does not discuss parameters. The single parameter 'record_url' is described in the schema as 'Full CiNii URL or CRID', but the description does not compensate for the low coverage. It adds nothing beyond the schema, so the agent must rely solely on the schema's minimal description.

    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 states a specific verb ('Fetch'), a resource ('single CiNii record'), and the two identifier forms ('by URL or CRID'), which clearly distinguishes it from the sibling search tools (cinii_search_*). It also notes the return envelope with operation 'get_record', making the tool's purpose unambiguous.

    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 implies usage: you need a specific URL or CRID, which differentiates it from the search siblings. However, it does not explicitly say 'use this when you have an identifier' nor name the alternatives. The context of siblings makes it clear enough, but explicit guidance is missing.

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

  • Behavior5/5

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

    The description adds meaningful behavioral detail beyond the annotations: records default to record_type 'article', mixed types are not always disambiguated, and a unified envelope is returned. This is exactly the kind of caveat an agent needs before relying on the output.

    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 compact and front-loaded: purpose first, then output envelope, then the critical record_type caveat. Every sentence earns its place with no filler.

    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?

    The output schema and annotations cover return shape and safety, and the description covers the important cross-type ambiguity. Parameter semantics are missing from the description, but the schema's property names, defaults, and constraints make invocation reasonably clear.

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

    Parameters1/5

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

    Schema description coverage is 0%, and the description does not explain query, lang, count, start, from_year, or to_year. With no parameter guidance in the description, it fails to compensate for the low schema coverage.

    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 identifies a specific operation: cross-type search across all CiNii content. 'All CiNii content' distinguishes this from the type-specific sibling tools without needing to open their schemas.

    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 gives clear context: use this for cross-type/all-content searching. It does not explicitly name alternatives or state when not to use it, but the scope is sufficiently explicit.

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

  • Behavior5/5

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

    Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering safety. The description adds substantial behavioral detail: it explains the ANDing of multi-word queries, the ZERO_CONJUNCTION diagnostic suggesting the query may be unindexed, the SCRIPT_LATIN_QUERY diagnostic for romanized-only searches, and the difference from J-STAGE full-text searching. This goes well beyond the annotations and gives the agent critical insights for interpreting results correctly.

    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 short paragraphs. The first sentence states the purpose and return envelope. The second paragraph packs three sentences of useful caveats. It is front-loaded with the core purpose and each subsequent sentence earns its place by clarifying search behavior or pointing to the right sibling tool. There is no fluff or repetition, making it highly concise and well-structured.

    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?

    The description covers the essential behavioral quirks that could lead an agent astray (zero results, romanized search, J-STAGE differences) and routes monographs to the correct tool. It does not explain the 'unified envelope' return format, but an output schema exists so that is acceptable. It also does not detail pagination or sorting semantics, but those are likely standard and inferable from the schema. The description is sufficient for effective use given the existing schema and annotations.

    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 has a description for the 'query' parameter, but the overall schema coverage is low (0% per signals, though query has a description). The description compensates by explaining how the query is interpreted (ANDs multi-word queries, may hit romanized metadata), which directly affects how to construct the query. It does not explain other parameters like sort, count, or filters, but those are standard and have defaults. Given the low coverage, the description adds meaningful semantic value for the most critical parameter, so a 4 is warranted.

    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 states 'Search CiNii Research for journal articles' — a specific verb and resource, clearly distinguishing it from the other CiNii tools. It also explicitly notes that monographs belong in cinii_search_books, reinforcing the boundary to sibling tools. This is unambiguous and immediately tells an agent what the tool does and what it does not cover.

    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 when-to-use context: it tells the agent that the article index is for journal articles and that monographs should be searched in cinii_search_books. It also warns about behavioral differences from J-STAGE, which helps the agent decide if this is the right search. However, it does not explicitly name all alternatives (e.g., cinii_search_all) nor provide a comprehensive when-not-to-use list, so it slightly lacks in guiding against other nearby tools.

    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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