초보자에게 친숙한 모델 컨텍스트 프로토콜(MCP) 서버로, 사용자가 MCP 개념을 이해하고, 대화형 예제를 제공하며, 사용 가능한 MCP 서버를 나열합니다. 이 서버는 MCP를 사용하는 개발자에게 유용한 도구로 설계되었습니다.
저자: qpd-v
📚 개념 설명 : 도구, 리소스, 프롬프트 등 MCP 개념에 대한 명확하고 초보자 친화적인 설명을 받아보세요.
🔍 서버 디렉토리 : 카테고리별로 정리된 사용 가능한 MCP 서버의 포괄적인 목록을 탐색하세요
💡 대화형 예제 : MCP 기능의 실제 예를 확인하세요
🛠️ 튜토리얼 프롬프트 : 첫 번째 MCP 도구 및 리소스를 만드는 단계별 가이드
Related MCP server: Learn MCP Server
지엑스피1
Claude Desktop 구성( claude_desktop_config.json )에 서버를 추가합니다.
{
"mcpServers": {
"mcp-guide": {
"command": "node",
"args": ["path/to/mcp-guide/dist/index.js"]
}
}
}Claude Desktop을 다시 시작하세요
사용 가능한 도구를 사용하세요.
explain_concept : MCP 개념에 대한 설명을 받으세요
show_example : MCP 기능의 실제 예를 확인하세요
list_servers : 카테고리별로 사용 가능한 MCP 서버를 검색합니다.
# Start the server
mcp-guide
# Or if installed locally
npx mcp-guide초보자에게 친숙한 MCP 개념 설명을 받아보세요.
개념 예시:
도구
자원
프롬프트
섬기는 사람
고객
서버 유형
프레임워크
고객
MCP 기능의 실제 예를 보여주세요.
예시 기능:
도구 호출
리소스_읽기
프롬프트_템플릿
카테고리별로 사용 가능한 MCP 서버를 나열합니다.
카테고리:
브라우저
구름
명령줄
의사소통
고객 데이터
데이터 베이스
개발자
데이터 과학
파일 시스템
재원
지식
위치
모니터링
찾다
여행하다
버전 제어
다른
# Clone the repository
git clone https://github.com/qpd-v/mcp-guide.git
cd mcp-guide
# Install dependencies
npm install
# Build the project
npm run build
# Start the server
npm start기여를 환영합니다! 풀 리퀘스트를 제출해 주세요.
이 프로젝트는 Apache License 2.0에 따라 라이선스가 부여되었습니다. 자세한 내용은 LICENSE 파일을 참조하세요.
[ ] 서버 목록에서 대화형 서버 설치
[ ] 더욱 상호작용적인 예제와 튜토리얼
[ ] 향상된 서버 분류 및 검색
Get a beginner-friendly explanation of an MCP concept
| Name | Required | Description | Default |
|---|---|---|---|
| concept | Yes | The MCP concept to explain (e.g., 'tools', 'resources', 'prompts', 'server', 'client', 'server_types', 'frameworks', 'clients') |
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. While 'Get' implies a read operation, the description doesn't address important behavioral aspects like whether this requires authentication, rate limits, what format the explanation returns, or if it's cached. For a tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate but lacks completeness. It doesn't explain what the output looks like (text format, length, structure) or provide behavioral context needed since annotations are absent. A 3 reflects the minimum viable level for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single parameter 'concept' with examples. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining the 'beginner-friendly' aspect relates to the output rather than parameter handling. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('Get') and resource ('explanation of an MCP concept'), and specifies the target audience ('beginner-friendly'). However, it doesn't distinguish this tool from its sibling tools (list_servers, show_example), which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 its siblings (list_servers, show_example). It doesn't mention any prerequisites, alternatives, or exclusions, leaving the agent with no contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List available MCP servers by category
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes | Server category to list (e.g., 'browser', 'cloud', 'command_line', 'communication', 'database', 'developer', 'filesystem', 'search', 'all') |
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 lists servers by category but doesn't describe what the output includes (e.g., server names, statuses, details), whether it's a read-only operation, potential rate limits, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 without unnecessary words. It's front-loaded with the core action ('List available MCP servers') and includes the key constraint ('by category'). Every part of the sentence contributes to understanding, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't cover what the output looks like (e.g., list format, data included), error handling, or behavioral traits like whether it's safe or has side effects. For a tool that likely returns structured data, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'by category', which aligns with the single parameter 'category' in the input schema. Since schema description coverage is 100% (the parameter has a clear description and enum values), the description adds minimal value beyond what the schema provides. It doesn't explain the semantics of categories (e.g., what 'all' means) or usage nuances, 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('available MCP servers'), specifying they are organized 'by category'. It distinguishes the tool's purpose from its siblings (explain_concept, show_example) by focusing on listing servers rather than explaining concepts or showing examples. However, it doesn't specify what 'available' means (e.g., installed, running, or discoverable), keeping it from 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.
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 doesn't mention prerequisites, context for selecting categories, or how it differs from potential sibling tools in usage scenarios. The agent must infer usage based solely on the tool name and description without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Show a practical example of an MCP feature
| Name | Required | Description | Default |
|---|---|---|---|
| feature | Yes | The MCP feature to demonstrate (e.g., 'tool_call', 'resource_read', 'prompt_template') |
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 'shows' an example, implying a read-only or display operation, but doesn't clarify aspects like output format, interactivity, or any constraints (e.g., rate limits, authentication needs). This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without unnecessary words or complexity. It is front-loaded and efficiently conveys the essential information, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one well-documented parameter and no output schema, the description is minimally adequate but lacks depth. It doesn't explain what the output entails (e.g., text, code snippet, interactive demo) or address behavioral traits, which is a gap given the absence of annotations. This makes it functional but incomplete for guiding an agent fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the 'feature' parameter with examples. The description adds no additional meaning beyond what the schema provides, such as elaborating on feature options or usage context. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately handles parameter semantics without extra description value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('show') and resource ('practical example of an MCP feature'), making it understandable. However, it doesn't explicitly distinguish itself from sibling tools like 'explain_concept' or 'list_servers', which might also involve demonstrating or explaining MCP features, leaving some ambiguity about its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'explain_concept' or 'list_servers'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone, which is insufficient for optimal selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0explain_conceptlist_serversshow_exampleScored across 3 tools
Each tool has a clearly distinct purpose with no overlap: explain_concept provides explanations, list_servers enumerates available servers, and show_example demonstrates practical usage. An agent can easily distinguish between these three functions.
All tools follow a consistent verb_noun pattern (explain_concept, list_servers, show_example) with clear, descriptive names. There are no deviations in naming style or conventions.
With only 3 tools, the server feels somewhat thin for a 'guide' purpose, which might suggest broader coverage. However, the tools are well-defined and cover core functions, making this borderline but not severely lacking.
The tools cover key aspects of an MCP guide: explanation, listing, and examples. Minor gaps might include advanced tutorials or troubleshooting, but the surface supports basic learning workflows effectively.
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