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matematicsolutions

mcp-eu-sparql

by matematicsolutions
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JavaScript
Remote

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.1.0

  • Disambiguation5/5

    Each tool targets a distinct search dimension: CELEX number, date range with type filter, and CJEU rulings. There is no overlap in functionality.

    Naming Consistency4/5

    Two tools follow 'search_by_<criterion>' pattern, while the third uses 'search_cjeu', which is slightly inconsistent but still clear and predictable.

    Tool Count4/5

    Three tools cover the core search needs for EU law (specific ID, date range, case law), though a keyword search tool could be added for completeness.

    Completeness3/5

    The set covers specific ID lookup, date-based filtering, and case law search, but lacks a general free-text keyword search, which is a notable gap for a legal research server.

  • Average 3.8/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 16 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.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

  • Add related servers to improve discoverability.

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.

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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

  • Behavior3/5

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

    Annotations already declare read-only, idempotent, not destructive. Description adds that it returns specific fields, but does not disclose pagination, sorting, or filtering by type. Adequate but not rich.

    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?

    Single sentence, front-loaded with purpose, no wasted words. Highly concise and 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?

    Describes return values (CELEX, date, title, URL) since no output schema. Covers all parameters with descriptions. Missing details on sorting or default behavior, but sufficient for basic use.

    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 covers all parameters with descriptions (100% coverage). Description adds no extra meaning beyond what schema provides, so baseline 3.

    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 the tool searches CJEU judgments and orders, with optional date filtering, and lists returned fields. It distinguishes from sibling tools by being a general search, though it does not explicitly differentiate.

    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?

    Implies usage for general CJEU search with optional date range, but no guidance on when to use sibling tools (search_by_celex, search_by_date_range) or exclusions.

    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 indicate read-only, idempotent, non-destructive operation. Description adds that it returns title and URL, but no further behavioral details like error handling or performance. Adequate given annotation coverage.

    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?

    Description is concise with three short sentences, each adding value: purpose, uniqueness, examples. No unnecessary words. Front-loaded with main action.

    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?

    For a simple lookup tool with comprehensive annotations and schema, the description covers purpose, parameters (via examples), return value (title + URL), and usage context. No gaps.

    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 coverage is 100%, so parameters are already described. Description adds CELEX examples and explains uniqueness, but does not significantly extend schema documentation. Baseline score of 3 is appropriate.

    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?

    Description clearly states the tool finds an EU legal act by CELEX number, with examples. It implicitly distinguishes from sibling tools (search_by_date_range, search_cjeu) by focusing on unique identifier lookup, but does not explicitly contrast them.

    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?

    Provides examples and emphasizes uniqueness of CELEX, but does not specify when to use alternatives or what to do if CELEX is unknown. Implied usage but lacks explicit 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?

    Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds a useful behavioral constraint (max 50 results per query), which goes beyond annotations. It does not describe pagination or return format, but the annotations cover the core safety profile.

    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, each adding value. Purpose is front-loaded, options and limits are stated concisely. No unnecessary words.

    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 tool has 5 parameters, 2 required, and no output schema. The description mentions max results and date range filtering, which is adequate. It does not explain ordering or error handling, but for a search tool with good annotations, this is nearly complete.

    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?

    All 5 parameters are documented in the schema (100% coverage). The description adds minimal extra value: it expands the type abbreviations (e.g., REG=rozporzadzenie) and clarifies that omitting type covers all. The baseline of 3 is appropriate since schema descriptions are already complete.

    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 finds EU legal acts within a date range, with optional type filtering. This distinguishes it from sibling tools 'search_by_celex' (by CELEX number) and 'search_cjeu' (Court of Justice documents).

    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 a clear use case (reviewing acts from a specific legislative period) and mentions optional filters and a maximum result limit. However, it does not explicitly state when not to use this tool or directly compare with siblings.

    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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