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🚀 MCP 로컬 개발

여러분이 놀라운 것을 만드는 데 집중하는 동안 AI가 로컬 개발 환경을 처리해 드립니다!

✨ 이게 뭐예요?

LLM이 개발 환경을 구성하고 관리할 수 있도록 지원하는 로컬 개발 환경 관리자입니다. AI 어시스턴트가 환경 설정, 종속성 관리 및 테스트를 자동으로 처리하도록 설계되었습니다.

Related MCP server: MCP Build Environment Service

🏃 빠른 시작

  1. MCP 빠른 시작 가이드 에서 Claude Desktop을 설치하세요

  2. Claude Desktop 구성에 다음을 추가하세요.

지엑스피1

  1. 클로드에게 GitHub 저장소를 알려주고 개발 환경을 설정해 달라고 요청하세요!

  2. 테스트를 실행하고 적용 범위를 보고하세요!

  3. 토론을 하거나, 이것저것 살펴보거나, 끝났으면 정리하세요!

🎯 핵심 기능

테스트 러너

  • 🧪 커버리지 보고 기능이 있는 pytest

  • ⚡️ V8 커버리지를 활용한 비테스트

  • 🃏 자세한 커버리지 지표를 제공하는 Jest

  • 🔬 커버리지 지원이 포함된 단위 테스트

런타임 지원

  • 🐍 UV 패키지 관리를 사용한 Python

  • 📦 NPM을 사용한 Node.js

  • ⚡️ Bun 런타임 및 패키지 관리자

환경 관리

  • 🏗️ 자동 런타임 감지

  • 📦 스마트 패키지 관리자 선택

  • 🔒 샌드박스 환경

  • 🧹 자동 정리

  • 🔄 GitHub 저장소 지원

  • 📂 지역 프로젝트 지원

개발자 경험

  • 🎯 구성이 필요 없음

  • 📊 구조화된 JSON 로깅

  • 🔍 자세한 테스트 커버리지 지표

  • 🛡️ 프로젝트별로 격리된 환경

💫 후드 아래

  • MCP 서버 사양 : 포괄적인 테스트 범위로 완벽한 준수

  • 경로 분리 : 각 환경은 깔끔하게 포함되어 있습니다.

  • 시스템 통합 : 설치된 런타임(Python, Node.js, Bun)을 사용합니다.

  • 패키지 관리 : 각 런타임에 대해 가장 빠른 사용 가능한 패키지 관리자를 자동으로 선택합니다.

  • 네트워크 액세스 : 패키지 관리를 위한 완벽한 연결성

  • 프로세스 처리 : 최대 속도를 위한 네이티브 시스템 프로세스

🌟 비하인드 스토리

개발에는 여러 모델에 대한 엄격한 테스트가 포함되었습니다.

  • 🏆 클로드 3.5 소네트: 망가졌어

  • 💪 DeepSeek V3: 강력한 성능

  • 👎 O1: 별로야, 밥

🚀 주요 내용

이 프로젝트는 AI 지원 개발의 놀라운 잠재력을 보여줍니다.

  • 🏃‍♂️ 초고속 프로토타입 제작

  • 🎯 마지막 15%는 여전히 실제 작업이 이루어지는 곳입니다.

  • 📚 실제 AI 개발 패턴의 훌륭한 예

💭 AI 및 개발에 대한 참고 사항

소프트웨어 개발에 수년간 종사해 온 사람으로서, 이 프로젝트에서 흥미로운 점은 단순히 자동화가 아니라 개발 환경과의 상호작용 방식의 변화입니다. 인간 개발자를 대체하는 것이 아니라 인지적 부담을 줄이는 데 가치가 있습니다. AI가 환경 설정 및 유지 관리를 담당하면 개발자는 아키텍처 및 디자인 결정에 더욱 집중할 수 있습니다.

이 프로젝트는 AI가 단순히 코드를 생성하는 것이 아니라 복잡성을 관리하는 것임을 보여줍니다. 개발 환경 설정의 기계적 측면을 처리함으로써, 인간의 통찰력이 진정으로 필요한 창의적이고 구조적인 과제에 집중할 수 있는 정신적 여유를 확보합니다.

🙏 큰 감사를 드립니다

  • UV - Speed Demon Python 패키지 설치 프로그램

  • Aider - AI 페어 프로그래밍 친구

  • Anthropic - Claude의 개발 지원에 대한 내용입니다.

  • Helix Editor - 최고의 모달 편집

📄 라이센스

MIT

Available Tools

4 tools
local_dev_cleanupC

Clean up a local development environment

ParametersJSON Schema
NameRequiredDescriptionDefault
env_idYesEnvironment identifier

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool performs cleanup but does not specify what actions are taken (e.g., destructive deletion, archiving, or resetting), potential side effects, permission requirements, or error handling. This leaves significant gaps in understanding the tool's behavior and risks.

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: 'Clean up a local development environment.' It is front-loaded with the core action and resource, with no unnecessary words or redundancy. Every part of the sentence contributes directly to the tool's purpose.

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's complexity (a cleanup operation likely involving destructive actions), lack of annotations, and no output schema, the description is insufficient. It does not explain what 'clean up' entails, what is returned (e.g., success status, logs), or any constraints. For a tool that could have significant side effects, more detail is needed to ensure safe and correct usage.

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?

The input schema has 100% coverage with one parameter ('env_id'), documented as 'Environment identifier.' The description does not add any parameter-specific details beyond the schema, but since there is only one parameter and schema coverage is high, the baseline is elevated. The description implies the parameter identifies the environment to clean up, which aligns with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose as 'Clean up a local development environment,' which is clear but vague. It specifies the verb ('clean up') and resource ('local development environment'), but lacks detail on what 'clean up' entails (e.g., deleting files, stopping processes, resetting configurations). It does not differentiate from sibling tools like 'local_dev_from_filesystem' or 'local_dev_run_tests,' which are unrelated operations.

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. It does not mention prerequisites, such as when cleanup is needed (e.g., after testing or before deployment), or exclusions, like avoiding use during active development. Without context, the agent must infer usage based on the tool name alone.

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

local_dev_from_filesystemC

Create a new local development environment from a filesystem path

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesLocal filesystem path

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool creates something but doesn't specify what 'local development environment' entails, whether it requires specific permissions, if it's destructive to existing environments, or what happens on failure. This leaves significant gaps for a creation 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?

The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a tool with one parameter and gets straight to the point without unnecessary elaboration.

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 creation tool with no annotations, no output schema, and siblings that suggest complex operations (cleanup, tests), the description is insufficient. It doesn't explain what constitutes a 'local development environment', what gets created, or what the expected outcome is. The agent lacks crucial context to use this tool effectively.

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 description coverage is 100%, with the single parameter 'path' documented as 'Local filesystem path'. The description adds no additional parameter information beyond what's in the schema. According to guidelines, when schema coverage is high (>80%), the baseline is 3 even with no param info in description.

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 action ('Create a new local development environment') and the resource ('from a filesystem path'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'local_dev_from_github' which serves a similar purpose but from a different source.

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 like 'local_dev_from_github' or 'local_dev_cleanup'. It lacks any context about prerequisites, when this approach is preferred, or what happens if the path is invalid. The agent must infer usage from the tool name alone.

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

local_dev_from_githubC

Create a new local development environment from a GitHub repository

ParametersJSON Schema
NameRequiredDescriptionDefault
github_urlYesGitHub repository URL

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a local dev environment but lacks details on permissions needed, whether it overwrites existing environments, error handling, or output format. This is a significant gap for a creation tool with zero annotation coverage.

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, clear sentence with zero wasted words, making it highly efficient and front-loaded. It directly communicates the core functionality without unnecessary elaboration.

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's complexity as a creation operation with no annotations and no output schema, the description is insufficient. It doesn't explain what the created environment entails, how to interact with it, or potential side effects, leaving critical gaps for an AI agent to use it effectively.

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 input schema has 100% description coverage, with the single parameter 'github_url' documented as 'GitHub repository URL'. The description adds no additional semantic context beyond this, such as URL format examples or validation rules, so it meets the baseline for high schema coverage.

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 action ('Create') and resource ('local development environment from a GitHub repository'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'local_dev_from_filesystem' or 'local_dev_cleanup', which would require mentioning the specific GitHub source distinction.

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 like 'local_dev_from_filesystem' or 'local_dev_cleanup', nor does it mention prerequisites or exclusions. It merely states what the tool does without contextual usage information.

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

local_dev_run_testsC

Auto-detect and run tests in a local development environment

ParametersJSON Schema
NameRequiredDescriptionDefault
env_idYesEnvironment identifier

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'auto-detect and run tests' but lacks details on permissions, side effects, error handling, or output format. This is inadequate for a tool that likely involves execution in a development environment.

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, efficient sentence that is front-loaded and contains no wasted words. It directly conveys the core functionality without unnecessary elaboration.

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 lack of annotations and output schema, and the tool's potential complexity (running tests in a local environment), the description is insufficient. It does not cover behavioral aspects, return values, or error cases, leaving significant gaps for the 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?

The input schema has 100% description coverage, with the 'env_id' parameter documented as 'Environment identifier'. The description does not add any further meaning or context about this parameter, so it meets the baseline for high schema coverage without extra value.

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 tool's purpose with a specific verb ('run tests') and resource ('in a local development environment'), and includes the 'auto-detect' capability. However, it does not explicitly differentiate from sibling tools like local_dev_cleanup or local_dev_from_github, which prevents a perfect score.

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 the sibling tools listed. There is no mention of prerequisites, context, or exclusions, leaving the agent with minimal usage direction.

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. Dates show when Glama detected each change.

  1. 4 tool updates
    • First observedlocal_dev_cleanup
    • First observedlocal_dev_from_filesystem
    • First observedlocal_dev_from_github
    • First observedlocal_dev_run_tests

TDQS

B3.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: cleanup, creation from filesystem, creation from GitHub, and running tests. There is no overlap in functionality, making it easy for an agent to select the correct tool for each specific task without confusion.

Naming Consistency5/5

All tool names follow a consistent 'local_dev_' prefix with descriptive suffixes (cleanup, from_filesystem, from_github, run_tests). This snake_case pattern is uniform throughout, making the tools predictable and easy to understand at a glance.

Tool Count4/5

With 4 tools, the count is reasonable for managing local development environments, covering key operations like setup, cleanup, and testing. It might be slightly lean for broader development tasks, but it's well-scoped for the apparent purpose without being overwhelming.

Completeness4/5

The toolset covers core lifecycle operations: creation (from two sources), cleanup, and testing. Minor gaps might include updating or monitoring environments, but the existing tools provide a solid foundation for basic local development workflows without significant dead ends.

Maintenance

ActivityInactive
ResponsivenessSyncing

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