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vertigooxyz-devix

Jira MCP Server

by vertigooxyz-devix
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TypeScript
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 are completely distinct: one lists issue types for discovery, the other creates an issue. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow the same 'jira_verb_noun' pattern (jira_list_issue_types, jira_create_issue), making the naming predictable and consistent.

    Tool Count3/5

    With exactly 2 tools, the server sits in the 'borderline thin' range. While the scope is clear, a Jira server typically needs more tools to be useful.

    Completeness2/5

    The tools cover only creation and issue-type lookup. Missing get, update, delete, search, and project listing means agents cannot verify or manage issues, leaving significant workflow gaps.

  • Average 4.9/5 across 2 of 2 tools scored.

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

    • No community issues 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 is passing

  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

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

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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

  • Behavior5/5

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

    Beyond the annotations (which already indicate a write operation), the description discloses authentication requirements (JIRA_EMAIL, JIRA_API_TOKEN), permission needs (403 error), and validation behavior (422). It also details return formats for both markdown and JSON, adding valuable context not present in 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 with clear sections (Args, Returns, Examples, Error Handling). It is concise yet comprehensive, with every sentence contributing actionable information. Front-loads the main purpose.

    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 no output schema, the description thoroughly explains return values for both formats. It covers prerequisites, error scenarios, and examples, making it complete for a creation tool with robust 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?

    Schema coverage is 100%, so baseline is 3. The description adds examples and clarifies that issue_type can be a name or numeric ID, reinforcing schema info with practical usage. Error handling explanations further enrich parameter context, justifying a 4.

    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 opens with 'Create a new Jira issue in a project,' clearly specifying the action and resource. It distinguishes itself from sibling tool jira_list_issue_types by focusing on creation, not listing.

    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 directs users to jira_list_issue_types for discovering valid issue types, providing clear guidance on when to use an alternative. Error handling section also helps users know what to do in failure scenarios.

    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 indicate readOnly, idempotent, and non-destructive, so the bar is lower. The description adds valuable context beyond that: error handling scenarios (401, 403, 404), return format details, and a note about permissions. These are genuine behavioral disclosures that help the agent anticipate outcomes.

    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 with clear sections (purpose, usage, args, returns, examples, errors). The first sentence immediately states the tool's function, and every sentence serves a purpose without redundancy. The error handling section is dense but valuable.

    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?

    There is no output schema, so the description compensates by specifying the return structure for both format options. It also covers error handling, usage context, and integration with jira_create_issue. For a simple listing tool, this is a complete and self-contained specification.

    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?

    Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema by providing explicit examples (e.g., "What issue types can I create in project PROJ?" -> project_key="PROJ") and clarifying the response_format default in a way that connects to use cases. This adds useful semantic guidance despite the schema being sufficient.

    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 opens with a specific verb+resource: "List issue types available for a Jira project." It clearly distinguishes from the sibling tool (jira_create_issue) by stating it is for discovery before creation, and the title itself is clear.

    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 explicitly says "Use this tool to discover which issue types can be used when creating issues" and "Use before jira_create_issue to get valid issue_type values." This provides clear when-to-use guidance and an alternative context, satisfying the dimension fully.

    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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  • Evaluate tool definition quality.

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