sonarqube-api-mcp

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct aspect of SonarQube (measures, quality gate, rules, issues, sources, projects) with no overlapping purposes. An agent can clearly differentiate between them.
Naming Consistency3/5
Tools mostly follow a verb_noun pattern, but there is inconsistency in the use of the 'sonar' prefix: some include it (get_sonar_fix_plan) while others do not (get_component_measures). This mixed style reduces clarity.
Tool Count5/5
Eight tools is well-scoped for a SonarQube API server, covering the core read operations without being excessive or insufficient.
Completeness4/5
The tool surface covers essential read-only operations (measures, quality gate, rules, issues, sources, projects). Minor gaps like a dedicated list_rules tool are present, but agents can work around using search_sonar_issues.
Average 3/5 across 8 of 8 tools scored. Lowest: 2.4/5.
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 status not available
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 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?
The description states the tool is 'read-only', which is a key behavioral trait. However, no annotations are provided, so the description carries the full burden. It fails to disclose other behaviors such as pagination behavior (the schema has pageSize with default 100, but not described), error handling, or rate limits. This is insufficient transparency.
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 sentence, which is concise but at the expense of necessary detail. It is front-loaded with the action and resource, but the lack of structure and additional information makes it less effective. For 12 parameters, more detail is needed while remaining concise.
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?
Given 12 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain the return format, sorting options, or any constraints like required permissions. An agent has insufficient context to use this tool reliably.
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%, meaning the input schema provides no descriptions for any of the 12 parameters. The description also offers no explanation of parameters like projectKey, severities, or logic for filtering. Without any semantic help, an agent cannot correctly invoke this tool with proper parameters.
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 verb 'search' and resource 'SonarQube issues', and notes it's read-only against a specific API endpoint. This adequately explains the tool's basic function. However, it does not differentiate from sibling tools like 'get_sonar_fix_plan' or 'search_sonar_projects', but the name itself is sufficiently specific.
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?
The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't mention cases where another tool like 'get_sonar_issue_context' might be more appropriate. With no usage notes or exclusions, an agent lacks context for correct selection.
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?
With no annotations, the description must fully disclose behavior but only states 'read-only'. It omits details about authentication, rate limits, or side effects, which is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is only one sentence, it is overly sparse and fails to include critical information, sacrificing completeness for brevity.
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?
Given 5 parameters, no output schema, and no annotations, the description is grossly incomplete. It lacks any context on parameter usage, return values, or operational constraints.
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?
The input schema has 0% description coverage, and the description does not explain any parameters (e.g., projectKey, metricKeys). This leaves the agent without necessary guidance on how to fill in the fields.
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 it gets SonarQube component measures for metric keys, using a specific verb and resource that distinguishes it from sibling tools like get_quality_gate_status or search_sonar_issues.
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?
The description provides no guidance on when to use this tool versus alternatives, such as search_sonar_projects or get_rule_details, leaving the agent to infer context without explicit direction.
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?
With no annotations, the description must disclose behavioral traits but only mentions 'read-only'. Missing effects of invalid inputs, rate limits, or authorization needs.
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?
Single sentence is concise and front-loaded, but given the lack of parameter guidance it feels under-specified rather than efficiently concise.
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?
For a tool with 4 optional parameters and no output schema, the description fails to explain how to construct a query or interpret results, leaving significant gaps.
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 adds no information about any of the 4 parameters, leaving their meaning and usage entirely ambiguous.
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?
Clearly states the tool retrieves read-only SonarQube quality gate status for a project. Uses specific verb and resource, differentiating it from sibling tools that focus on measures, rules, etc.
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 read-only usage but provides no explicit guidance on when to use this tool versus alternatives, nor any prerequisites such as required project key.
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?
With no annotations, the description must fully disclose behavior. Only states 'read-only' which is already implied by the verb. Missing details on error handling, rate limits, authentication, or what happens with invalid ruleKey.
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?
A single sentence is concise but too minimal. It lacks necessary details to be truly helpful. Structure is front-loaded but insufficient for the information content.
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?
The description does not explain the return value or differentiate from sibling tools effectively. Given the simplicity (1 param, no output schema), it could be complete with minimal addition but falls short.
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%, yet the description provides no information about the 'ruleKey' parameter. The parameter's purpose (e.g., format or examples) is absent, leaving the agent to infer from the schema alone.
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?
Clearly states verb 'Get', resource 'rule details', and specifies 'read-only' to indicate safe operation. The tool's purpose is distinct from sibling tools like search_sonar_issues or get_component_measures.
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 read-only rule details but provides no explicit guidance on when to use this tool versus alternatives like search_sonar_issues or get_component_measures. No when-not-to-use or prerequisite information.
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?
No annotations exist; description lacks behavioral details such as pagination via pageSize, read-only nature, or what happens with empty queries. Minimal 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?
Single sentence with no redundant information. Efficient and to the point.
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?
Without annotations or output schema, description should cover pagination and result interpretation. It only covers query purpose, leaving pageSize and output undefined.
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%. Description adds meaning for query (by name or key) but ignores pageSize, which has default and max. Incomplete parameter guidance.
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?
Description clearly states the tool finds SonarQube project keys by name or key, using specific verb and resource. It distinguishes from sibling tools like search_sonar_issues which targets issues.
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 on when to use this tool vs alternatives like get_quality_gate_status or get_component_measures. Lacks context for selection.
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?
With no annotations, the description must disclose behavioral traits, but it only indicates a read operation ('Get'). It omits details like authentication requirements, error handling for invalid keys, or any side effects, which is insufficient for a tool with no other behavioral documentation.
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, 14-word sentence that efficiently conveys the core function. It is front-loaded with the verb and resource. However, it could be slightly more informative without becoming verbose, e.g., mentioning the optional parameters briefly.
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 5 parameters, no output schema, and no annotations, the description is incomplete. It does not explain how contextLines affects output, what includeRule does, or how branch/pullRequest filter results. The return format is also unmentioned.
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 coverage is 0%, so parameters are undocumented in the schema itself. The description adds minimal value by hinting at context lines ('source lines around the affected range'), but does not explain the roles of branch, pullRequest, or includeRule, leaving them underspecified.
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 retrieves a single SonarQube issue with surrounding source lines, using specific verb 'Get' and resource 'one SonarQube issue'. It effectively distinguishes from sibling tools like search_sonar_issues (multiple issues) or get_sonar_sources (raw source without issue context).
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 retrieving a specific issue with context lines but does not explicitly state when to use this over siblings. No exclusions or alternatives are provided, leaving the agent to infer based on the tool's purpose.
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?
No annotations are provided, and the description only states what the tool returns. It does not disclose any behavioral traits like authorization needs, rate limits, or side effects, which is insufficient for a tool with 15 parameters.
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?
One sentence conveys the core action and scope, but it is dense and could be split for readability. Still efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description gives only a high-level shape (grouped by file, optional source context). It lacks details on response structure and parameter explanations, leaving many gaps for a tool with 15 parameters.
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?
The schema has 0% description coverage and 15 parameters, but the description does not explain any parameter meaning or behavior. Parameters like impactSeverities, impactSoftwareQualities, and contextLines remain ambiguous without schema descriptions.
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 it returns unresolved SonarQure issues grouped by file with optional source context for two scopes (new-code or overall-code). This differentiates it from siblings like search_sonar_issues or get_sonar_issue_context.
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 when a fix plan aggregated by file is needed, but does not explicitly exclude cases or mention alternatives. It is clear enough given sibling tool names.
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?
The description mentions 'read-only,' indicating non-destructive behavior. However, with no annotations, it lacks detail on permissions, output format, or edge cases (e.g., empty results).
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, no redundant text, front-loaded with the essential action. Efficient and clear.
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?
With 5 parameters, no output schema, and no annotations, the description is too brief. It omits details on return value, optional vs required parameters, and usage constraints.
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 has zero description coverage (0%), so description must compensate. It fails to explain the meaning of 'component,' 'from,' 'to,' 'branch,' or 'pullRequest,' offering little beyond the schema itself.
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?
Description clearly states 'Get read-only SonarQube source lines for a component,' specifying verb, resource, and context. It distinguishes from sibling tools by focusing on source lines.
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?
Description implies usage when source lines are needed but provides no explicit guidance on when to use this tool versus alternatives (e.g., searching for source, fetching measures). No exclusions or context are mentioned.
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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