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by cqfn

Aibolit용 MCP 서버, Java 코드 분석기

Rultor.com의 DevOps

만들다 코드코브 히트 오브 코드 특허

Claude Code , Cursor , Windsurf 와 같은 AI 에이전트를 사용하여 코드 리팩토링을 한다면 이 MCP 서버를 유용하게 활용할 수 있습니다. AI 에이전트에게 "코드 개선"을 요청하면 정확히 무엇을 개선해야 할지 고민할 수 있습니다. 안타깝게도 중요한 문제를 간과하는 경우가 많습니다. AI 에이전트는 설계상 "쉽게 해결할 수 있는" 외형적인 문제에 더 많은 관심을 기울입니다. 이 MCP 서버는 에이전트에게 코드에서 가장 중요한 디자인 문제가 무엇인지에 대한 힌트를 제공합니다. 그러면 에이전트가 해당 문제를 리팩토링하여 해결합니다.

먼저 Node , Npm , Python , Pip , aibolit을 설치합니다.

지엑스피1

그런 다음, 이 MCP 서버를 Claude Code 에 추가합니다(또는 간단히 ~/claude.json 편집해도 되지만 권장하지는 않습니다).

claude mcp add aibolit npx aibolit-mcp-server@0.0.4

그런 다음 Claude Code를 다시 시작하고 다음과 같이 질문합니다. "내 코드베이스에서 가장 중요한 디자인 문제를 찾아 수정하세요."

기여 방법

이 프로젝트를 테스트하려면 다음 명령을 실행하기만 하면 됩니다( Node 18 이상, Npm , GNU make가 설치되어 있어야 합니다).

npm install
make

변경 후 모든 것이 올바르게 빌드되면 풀 리퀘스트를 제출하세요.

Available Tools

1 tool
find_the_most_critical_design_issueA

Analyze one Java file. Find the most serious design flaw. It must need immediate refactoring. Ignore cosmetic or minor issues. Fix the one problem that will best improve code quality. Code quality means maintainability, readability, loose coupling, and high cohesion. Point out the problem and where it is in the file.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYes

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description partially discloses behavior: it analyzes one Java file, ignores cosmetic issues, and identifies the problem with its location. However, it does not specify whether the tool is read-only or if it makes changes, nor how the analysis is performed or what the output format is.

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 extremely concise at 6 sentences, front-loaded with the core action, and each sentence adds unique value: scope, focus, exclusion criteria, quality definition, and output. No redundant or unnecessary information.

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?

The description is adequate for a simple tool with one parameter and no output schema, explaining the core function clearly. However, it lacks details on output format, performance expectations, or edge cases (e.g., empty file, multiple flaws), which would enhance completeness given the tool's analytical nature.

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 only parameter is 'path', and the description clarifies it expects a Java file path, adding context beyond the bare schema. However, it does not detail the format or any constraints on the path, and schema description coverage is 0%, so the description provides minimal additional meaning.

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 tool name and description clearly indicate the tool identifies the most serious design flaw in a Java file, emphasizing critical issues over cosmetic ones. It distinguishes itself from a general code review tool by focusing on immediate refactoring needs.

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 specifies when to use the tool (to find critical design issues) and provides criteria for what constitutes a serious flaw (maintainability, readability, loose coupling, high cohesion). It implicitly advises against using it for minor issues, and with no sibling tools, this provides sufficient context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • Changedfind_the_most_critical_design_issue1 field changed
      • removedInput schema / additionalProperties
        Removed value: -false
  2. 1 tool update
    • First observedfind_the_most_critical_design_issue

TDQS

A3.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap. The tool's purpose is clearly defined.

Naming Consistency5/5

Single tool, so no inconsistency. The name follows a verb_noun pattern (find_issue).

Tool Count3/5

One tool for a specific purpose (finding design issues in one file) is borderline but acceptable for a narrow scope.

Completeness2/5

The server only covers a single operation (analyze one file for one issue). Lacks features like batch processing, multiple issue types, or suggestions, leaving significant gaps for a design review tool.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

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