SonarLint MCP Server

by nielspeter

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Server Quality Checklist

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Latest release: v0.5.5
Disambiguation5/5
Each tool has a clearly distinct purpose: checking snippets vs single file vs multiple files, fixing all vs single issue, health check, and listing rules. No ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (check_code, check_files, check_quality, fix_all_issues, fix_issue, health_check, list_rules) using snake_case.
Tool Count5/5
7 tools is well-scoped for a code quality server, covering analysis, fixing, health, and rule listing without being too few or too many.
Completeness4/5
Covers core operations: code checking (snippet, single, batch), fixing (all or specific), health monitoring, and rule listing. Minor gaps like per-rule details, but overall complete.
Average 4.2/5 across 7 of 7 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
- Last stable release on May 12, 2026
- 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"
  ]
}
```
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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explains the output format (exact line numbers, severity, quick fixes) and scope (bugs, code smells, etc.), implying a read-only analysis. Lacks details on potential side effects or permissions but is sufficient.
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?
All five sentences serve a purpose: defining the task, providing an analogy, stating when to use, describing output, and giving an alternative for multiple files. No wasted 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?
For a tool with 3 parameters, no output schema, and no annotations, the description covers purpose, usage, and output format adequately. It lacks explicit mention of return type or error cases but is sufficient for selection.
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 description coverage is 100%, so baseline is 3. The description adds no additional semantic info beyond the schema's parameter descriptions.
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 checks a file for code quality issues, listing types. It distinguishes from sibling 'check_files' for multiple files, but does not explicitly differentiate from 'check_code' which is a sibling.
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?
It provides explicit when to use ('after writing or modifying code') and when not to use ('For multiple files use check_files'), but does not mention alternatives like check_code or fix tools.
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?
Without annotations, description covers effects (applies fixes), return info (what fixed/remains), and limitation (manual fixes needed). Lacks details on undo or permissions, but adequate.
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, no fluff, main purpose first, each sentence adds value.
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 simple tool with one param and no output schema, description covers key aspects: what it does, how, and limitations. Could mention if it commits changes, but not necessary.
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%, description adds no extra meaning to the filePath parameter beyond what the schema provides.
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 fixes all code quality issues with available quick fixes in a file, using SonarLint. It distinguishes from sibling fix_issue by targeting all issues at once.
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?
Implies when to use (bulk fix) and notes some issues require manual fixes, but lacks explicit when-not or alternative tools. Still provides enough context for an agent.
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?
The description discloses that 'the file is modified directly' and that it applies a SonarLint-suggested fix. With no annotations provided, this transparency is valuable. No mention of what happens on failure, but acceptable for a simple tool.
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 sentences, front-loaded with purpose, followed by behavioral detail and alternative tool. No wasted 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?
Given the three required parameters and no output schema, the description adequately covers the action and behavior. It could mention what happens on success or failure, but the tool is straightforward.
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 description coverage is 100%, so baseline is 3. The description mentions the three parameters (file, line, rule) but adds no additional meaning beyond the 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 starts with a clear verb ('fix') and resource ('one specific code quality issue'), and is explicitly distinguished from the sibling tool fix_all_issues. It states it applies SonarLint-suggested fix, providing precise scope.
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 explicit guidance: use this tool for one issue, and use fix_all_issues for all issues. It does not mention when not to use (e.g., if review is needed), but the context is clear.
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?
No annotations, but description reveals read-only nature (health check) and lists returned data. Lacks explicit safety or side-effect info, but adequate for a simple query.
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 sentences: first states purpose and outputs, second gives usage scenario. No fluff, front-loaded with critical info.
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 parameterless health check without output schema, description covers purpose, outputs, and usage. Completeness is sufficient given simplicity.
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?
No parameters exist, so schema coverage is 100%. Baseline score of 4 applies as description adds no parameter details by necessity.
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 specifies the tool checks backend health and shows plugins, cache stats, version. Distinct from sibling tools like check_code or fix_issue.
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?
States explicit use case: 'diagnose when analysis isn't working as expected.' Provides clear context without needing exclusions for a health check.
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?
No annotations are provided, so the description carries full burden. It correctly implies read-only behavior and mentions the types of issues covered (bugs, code smells, vulnerabilities, hotspots). It lacks details on pagination or performance, but for a simple list, it is sufficiently transparent.
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 three sentences long, front-loaded with the main purpose, and contains no redundant information. Every sentence adds value.
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?
There is no output schema, so the description must compensate. It mentions the return fields (ID, name, severity) and categories, but it does not fully specify the output structure (e.g., whether category is a separate field). It is mostly complete for a list tool but could be slightly more explicit.
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?
The schema has one parameter 'language' with 100% description coverage (enum and description provided). The description does not add new information about the parameter beyond what the schema already states, so 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 verb 'List' and the resource 'active code quality rules' with specific attributes (ID, name, severity). It also distinguishes the tool from sibling tools like check_code and fix_issue, which have different purposes.
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 use cases (look up rule meaning, discover issues, see language applicability). However, it does not explicitly state when not to use this tool or mention alternatives, though the context of sibling tools implies differentiation.
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?
Without annotations, the description carries the burden. It describes the tool as analyzing code quality and catching issues, implying a read-only operation. However, it does not explicitly state that no modifications are made, though 'No file on disk needed' suggests no file changes. Slight room for improvement.
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 sentences, front-loaded with purpose, followed by use cases. No superfluous information. Every sentence is necessary.
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 three parameters and no output schema, the description covers what the tool does and when to use it. However, it does not describe the output format (e.g., report), which would be helpful for an agent. Overall adequate but not fully 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?
Schema coverage is 100% with descriptions for all parameters. The description adds context like 'code snippet or content you have in hand' but does not significantly enhance understanding beyond the schema. Baseline of 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 tool checks code quality, catches bugs, code smells, security issues, and complexity problems. It distinguishes itself from siblings by specifying 'No file on disk needed', making it unique among tools like check_files.
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 provides when to use: 'validate code before writing it to disk, review generated code, or check code you've read into context'. Also implies when not to use by stating 'No file on disk needed'.
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?
No annotations are provided, so the description bears full responsibility. It discloses key behavioral traits: supports glob patterns, requires basePath for relative paths, output is compact showing only files with issues, and clean files get a summary count. This gives the agent a good understanding of the tool's behavior.
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 efficiently structured: first sentence states purpose, second gives usage context, third explains glob and output format. Every sentence adds value, and the length is appropriate for the complexity.
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 has 5 parameters and no output schema, the description covers the main behaviors: multi-file support, glob patterns, compact output, and the alternative for single file. It could mention what happens when no issues are found (implied by 'summary count') but overall it is sufficiently complete for an experienced agent.
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 description coverage is 100%, so baseline is 3. The description adds context about glob patterns and basePath usage but does not significantly enhance the understanding of each parameter beyond what the schema already provides. For example, minSeverity and excludeRules are well-described in 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 tool checks multiple files for code quality issues (bugs, code smells, security vulnerabilities). It specifies the resource ('multiple files') and the action ('check'), and distinguishes itself from the sibling tool 'check_quality' which is for a single file.
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?
Explicit guidance is given: 'Use when reviewing or modifying several files.' It also provides a negative case: 'For a single file use check_quality.' Additionally, it explains when to provide basePath and supports glob patterns, helping the agent decide when to use this tool.
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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