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matematicsolutions

cz-eli-mcp

by matematicsolutions
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Server Quality Checklist

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

  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: metadata retrieval, full text retrieval, and search. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow a consistent `cz_verb_noun` pattern in snake_case, making them predictable and easy to understand.

    Tool Count5/5

    Three tools is well-scoped for a legal acts server, covering the core operations without unnecessary bloat.

    Completeness4/5

    The set covers search, metadata, and full text retrieval. A list-all-act function is missing but search can approximate it; otherwise complete for read-only access.

  • 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
    • 14 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under Apache 2.0.

  • 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.

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

  • Behavior3/5

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

    Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds that the text is assembled from ordered HTML fragments of the latest consolidated version, which provides useful context beyond annotations but does not fully explain behavior like output format or permissions.

    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 concise with two sentences: the first clearly states the purpose, and the second adds a key detail about the assembly. Every sentence earns its place with no fluff.

    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?

    Given the tool's simplicity (2 params, output schema present, rich annotations), the description adequately covers what it does and how it works. The presence of an output schema reduces the need to detail return values. It could mention how the text is returned (e.g., plain text or HTML) but that is likely covered by the output schema.

    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% (both year and number are described in the input schema). The description does not add any additional meaning or constraints beyond the schema, so it meets the baseline of 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 it fetches the full consolidated text of a Czech act by year and number, using a specific verb and resource. However, it does not explicitly differentiate from sibling tools like cz_get_act or cz_search, which could cause confusion.

    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 the siblings. The description does not include any when-to-use or when-not-to-use advice, leaving the agent to guess.

    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, idempotentHint, and destructiveHint. The description adds no behavioral traits beyond what is in annotations or schema. It is adequate but does not enhance 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?

    A single, clear sentence that immediately conveys the tool's purpose. No wasted words.

    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 simple input schema, output schema existence, and annotations covering behavioral safety, the description is complete enough for an agent to understand and invoke the tool correctly.

    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 baseline is 3. The description restates 'by year and number' but adds no additional meaning or constraints beyond 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 clearly states the action (Fetch), resource (Czech act metadata), and identifiers (year and number). It distinguishes from siblings like cz_get_text and cz_search by specifying 'metadata'.

    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 when you have year and number, but does not explicitly state when to prefer this over siblings or provide exclusions. The sibling names hint at alternatives, but the description itself lacks guidance.

    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 as false, covering the safety and behavior profile. The description does not add any behavioral details beyond the search intent, such as case-insensitive matching or pagination behavior. It is adequate but does not leverage the opportunity to provide context beyond 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 a single concise sentence that front-loads the core purpose: searching Czech acts by year and/or citation substring. No superfluous words; every part earns its place.

    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 presence of a full output schema, detailed input schema descriptions, and rich annotations, the description is complete enough. It covers what the tool does and the key search criteria, which is sufficient for an agent to decide when to use it.

    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 every parameter has a description in the schema. The description reiterates the two primary filtering parameters (year and contains) but does not mention limit or offset. This adds some context by summarizing the main criteria, but does not provide additional semantics beyond the schema. Baseline 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 clearly states the action (search), the resource (Czech acts), and the criteria (year and/or citation substring). It distinguishes from sibling tools 'cz_get_act' and 'cz_get_text', which retrieve specific acts or texts, by focusing on search functionality.

    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 directly tells the user to use this tool for searching Czech acts by year or citation substring. It implies the primary use case but does not explicitly state when to avoid this tool or when to use siblings instead. The verb 'search' clearly differentiates from 'get' siblings, so guidance is clear but not exhaustive.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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