MCPet: AI 시대를 위한 향수 어린 가상 반려동물 경험! 이 모델 컨텍스트 프로토콜(MCP) 서버를 통해 당신의 보살핌에 따라 진화하는 나만의 디지털 반려동물을 입양하고, 키우고, 함께 놀 수 있습니다. 먹이를 주고, 씻기고, 함께 놀고, 아기에서 어른으로 성장하는 모습을 지켜보세요. 반려동물의 능력치는 당신이 없을 때에도 시간이 지남에 따라 변화합니다. 마치 클래식 다마고치 장난감처럼, 모델 컨텍스트 프로토콜을 통해 최신 AI가 구동합니다. 지금 바로 당신의 디지털 친구를 입양하세요!
가상 반려동물 시뮬레이션 시스템을 구현하는 TypeScript 기반 MCP 서버입니다. 반려동물 관리 및 상호작용을 위한 도구를 제공하여 핵심 MCP 개념을 보여줍니다.
네 가지 애완동물 유형 중에서 선택하세요:
고양이 - 약간 변덕스럽지만 사랑스럽다
개 - 활기차고 항상 당신을 만나서 기뻐요
드래곤 - 독특하고 열정적인 성격
외계인 - 신비롭고 호기심 많은
애완동물이 4단계로 진화하는 모습을 지켜보세요.
아기 - 작고 연약한 아기
아이 - 성장하고 장난기 가득
10대 - 활력이 넘치고 발전적입니다.
성인 - 완전히 성장하고 현명함
5가지 핵심 통계를 관리하여 애완동물을 돌보세요.
배고픔 - 애완동물에게 충분한 배고픔을 유지하세요
행복 - 애완동물과 놀아주어 행복하게 유지하세요
건강 - 다른 통계에 의해 영향을 받는 전반적인 웰빙
에너지 - 활동으로 소모되고 휴식으로 보충됩니다.
청결 - 정기적인 목욕은 애완동물을 상쾌하게 유지합니다.
create_pet - 사용자 정의 이름과 유형으로 새로운 애완동물을 입양하세요
check_pet - 반려동물의 현재 상태와 통계를 확인하세요
feed_pet - 다양한 사료 옵션으로 애완동물에게 먹이를 주세요:
간식 - 약간의 배고픔을 해소
식사 - 균형 잡힌 영양
잔치 - 최대로 먹음 (하지만 건강에 해로울 수 있음)
play_with_pet - 다양한 게임을 플레이하세요:
볼 - 가벼운 운동
체이스 - 에너지 넘치는 재미
퍼즐 - 정신 자극
clean_pet - 애완동물을 목욕시켜 청결을 되찾으세요
put_to_bed - 애완동물이 잠을 자게 하여 에너지를 회복하세요
각 애완동물 유형 및 활동에 대한 동적 ASCII 아트 애니메이션
무작위 프레임은 생동감 있고 매력적인 경험을 만들어냅니다.
다음을 위한 특별 애니메이션:
다양한 음식을 먹다
다양한 게임을 플레이하다
입욕
자고 있는
아프다
그리고 더 많은 것들!
Related MCP server: buddy-mcp
종속성 설치:
지엑스피1
서버를 빌드하세요:
npm run build자동 재빌드를 사용한 개발의 경우:
npm run watchSmithery를 통해 Claude Desktop용 MCPet을 자동으로 설치하려면:
npx -y @smithery/cli install @shreyaskarnik/mcpet --client claudeClaude Desktop과 함께 사용하려면 서버 구성을 추가하세요.
MacOS의 경우: ~/Library/Application Support/Claude/claude_desktop_config.json Windows의 경우: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"mcpet": {
"command": "node",
"args": ["/path/to/mcpet/build/index.js"],
"env": {
"PET_DATA_DIR": "/path/to/writable/directory"
}
}
}
}참고: PET_DATA_DIR 환경 변수는 반려동물 데이터가 저장될 위치를 지정합니다. 쓰기 권한이 있는 디렉터리인지 확인하세요.
MCP 서버는 stdio를 통해 통신하므로 디버깅이 어려울 수 있습니다. MCP Inspector 사용을 권장합니다.
npx @modelcontextprotocol/inspector node /path/to/mcpet/build/index.js검사관은 애완동물 상호작용을 직접 테스트할 수 있는 인터페이스를 제공합니다.
클로드에게 다음과 같은 질문을 해보세요.
"위스커스라는 이름의 고양이 애완동물을 만들 수 있나요?"
"내 애완동물은 어떻게 지내요?"
"반려동물에게 밥을 줄 수 있나요?"
"반려동물과 쫓아다니며 놀고 싶어요"
"제 애완동물이 더러워 보이는데, 목욕시켜 주실 수 있나요?"
"제 애완동물이 피곤해 보이는데, 잠자리에 들게 해 주시겠어요?"
Check on your virtual pet's status
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 checks status but doesn't reveal whether this is a read-only operation, has side effects, requires authentication, or has rate limits. The description is minimal and misses key behavioral context needed 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose. It's appropriately sized for a simple tool with no parameters, though it could be slightly more informative without losing conciseness. No wasted words or redundant 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 simplicity (0 parameters, no output schema), the description is incomplete. It doesn't explain what status information is returned, format of response, or error conditions. For a status-checking tool in a pet management system, users need to know what metrics are available (health, hunger, etc.) 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 tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. Baseline score of 4 applies for zero-parameter tools when the description doesn't attempt to explain non-existent parameters.
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 states the tool's purpose as checking a virtual pet's status, which is clear but vague about what specific status information is retrieved. It distinguishes from siblings like feed_pet or play_with_pet by focusing on status checking rather than interaction, but doesn't specify what aspects of status are included (e.g., health, happiness, energy).
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 (e.g., whether a pet must exist), frequency recommendations, or relationship to other tools like create_pet (for initialization) or clean_pet (for maintenance). 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.
Clean your virtual pet
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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. 'Clean your virtual pet' suggests a mutation operation that might affect the pet's state, but it doesn't disclose whether this requires specific conditions, has side effects, or what the expected outcome is. The description lacks details on permissions, reversibility, or any behavioral traits beyond the basic action.
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 'Clean your virtual pet' is a single, efficient sentence that directly states the tool's purpose without any waste. It's appropriately sized for a simple tool and front-loaded with the essential action, making it easy to parse 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?
Given the tool has no parameters, no output schema, and no annotations, the description is minimal. While it states the action, it lacks context about what 'clean' means operationally, how it differs from sibling tools, or what the result entails. For a mutation-like tool in a pet care context, more detail on effects or usage would improve completeness.
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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. This meets the baseline for tools with no parameters, as there's nothing to compensate for.
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 'Clean your virtual pet' states a clear action (clean) on a specific resource (virtual pet), which meets the basic requirement. However, it doesn't distinguish this tool from its siblings like 'feed_pet' or 'play_with_pet' beyond the different action verb, leaving some ambiguity about what 'clean' specifically entails compared to other pet care actions.
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 like 'feed_pet' or 'check_pet'. It implies usage in the context of pet care but offers no explicit when/when-not scenarios or prerequisites, leaving the agent to infer context without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Create a new virtual pet
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name for your new pet | |
| type | Yes | Type of pet: cat, dog, dragon, or alien |
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 pet but doesn't explain what 'virtual' entails, whether this is a one-time or repeatable action, what happens on success/failure, or any side effects like resource consumption. This leaves significant gaps for a mutation tool.
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 any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.
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 that this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like what the tool returns, error conditions, or how it interacts with sibling tools, leaving the agent with insufficient context for reliable use.
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 schema description coverage is 100%, with clear descriptions for both parameters, including an enum for 'type'. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score without adding extra 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 action ('Create') and resource ('new virtual pet'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'check_pet' or 'feed_pet' beyond the creation aspect, 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.
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 'check_pet' or 'feed_pet'. It lacks context about prerequisites, such as whether a pet must be created before using other tools, or any exclusions for usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Feed your virtual pet
| Name | Required | Description | Default |
|---|---|---|---|
| food | Yes | Type of food: snack, meal, or feast |
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. 'Feed your virtual pet' implies a mutation (feeding changes pet state), but it doesn't specify what effects occur (e.g., increases energy, affects mood), whether it's idempotent, or any side effects like cooldowns. This leaves critical behavioral traits undocumented, making it inadequate for a mutation 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single sentence 'Feed your virtual pet', which is front-loaded and wastes no words. However, it's overly brief, bordering on under-specification, as it lacks necessary details for a mutation tool. While efficient, it could benefit from slightly more context without sacrificing brevity.
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 complexity as a mutation with no annotations and no output schema, the description is incomplete. It doesn't explain what feeding does (e.g., returns pet status or success message), potential errors, or behavioral nuances. For a tool that likely changes state, this leaves too many gaps, making it inadequate for effective use without additional inference.
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 adds no parameter semantics beyond what the input schema provides. The schema has 100% coverage with a clear description and enum for the 'food' parameter, detailing types like 'snack', 'meal', or 'feast'. Since the schema does the heavy lifting, the baseline score is 3, as the description doesn't compensate or add extra meaning, but it also doesn't contradict the schema.
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 'Feed your virtual pet' clearly states the action (feed) and target (virtual pet), providing a basic purpose. However, it doesn't distinguish this tool from sibling tools like 'play_with_pet' or 'put_to_bed' beyond the obvious action difference, nor does it specify what feeding accomplishes (e.g., increases happiness or health). This makes it vague in context, as it lacks sibling differentiation and specific outcomes.
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 offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., pet must be awake or hungry), exclusions (e.g., don't use if pet is full), or comparisons to siblings like 'check_pet' for status monitoring. Without such context, users must infer usage from the tool name alone, which is insufficient for informed selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Play with your virtual pet
| Name | Required | Description | Default |
|---|---|---|---|
| activity | Yes | Type of play activity: ball, chase, or puzzle |
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 action ('Play') but doesn't describe effects (e.g., how it affects pet happiness, energy levels, or other states), side effects, or constraints (e.g., cooldowns, limitations based on pet type). This leaves significant gaps for a tool that likely modifies pet state.
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 with no wasted words. It's front-loaded with the core action and target, making it easy to parse quickly. Every word contributes directly to conveying the tool's purpose.
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 complexity of a pet interaction tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after playing (e.g., changes to pet attributes, possible errors, or return values), leaving the agent without crucial context for effective use. This is inadequate for a tool that likely involves state changes.
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 'activity' parameter with an enum and description. The description adds no additional parameter information beyond what the schema provides, such as explaining the impact of different activity choices. Since schema coverage is high, the baseline score of 3 is appropriate.
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 'Play with your virtual pet' states a clear action ('Play') and target ('virtual pet'), but it's somewhat vague about what 'play' entails compared to other pet interactions. It distinguishes from siblings like 'feed_pet' or 'clean_pet' by focusing on play, but doesn't specify how it differs from other interactive tools beyond the general concept.
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 (e.g., if the pet must be awake or healthy), exclusions (e.g., not to use if the pet is sleeping), or comparisons to sibling tools like 'check_pet' for status monitoring. Usage is implied by the name but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Put your virtual pet to sleep to restore energy
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 action ('put to sleep') and outcome ('restore energy'), but doesn't describe side effects (e.g., does this make the pet unavailable for other actions?), time requirements, or success conditions. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
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 front-loads the key action and purpose. Every word earns its place: 'Put your virtual pet to sleep' specifies the action, and 'to restore energy' clarifies the goal. There is no redundancy or unnecessary elaboration.
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 complexity (simple mutation with no parameters) and lack of annotations/output schema, the description is minimally adequate. It explains what the tool does but doesn't cover behavioral details like side effects or energy restoration mechanics. For a mutation tool, more context on outcomes or constraints would improve completeness.
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 tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. Baseline is 4 for zero-parameter tools when the description is adequate for the action.
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 action ('put to sleep') and the resource ('virtual pet'), with the specific purpose 'to restore energy'. It distinguishes from siblings like 'check_pet' or 'play_with_pet' by focusing on energy restoration rather than status checking or entertainment. However, it doesn't explicitly contrast with all siblings (e.g., 'feed_pet' might also restore energy).
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 implies usage context ('to restore energy'), suggesting this tool should be used when the pet's energy is low. However, it doesn't provide explicit guidance on when NOT to use it (e.g., if the pet is already sleeping) or mention alternatives like 'feed_pet' for energy restoration. The context is clear but lacks exclusion criteria or sibling comparisons.
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.
v1.0.0check_petclean_petcreate_petfeed_petplay_with_petput_to_bedScored across 6 tools
Every tool has a clearly distinct purpose with no ambiguity: create_pet initializes a new pet, while check_pet monitors status, and feed_pet, clean_pet, play_with_pet, and put_to_bed each handle specific care actions. The descriptions reinforce unique functions, making misselection unlikely.
All tools follow a consistent verb_noun pattern with snake_case, such as check_pet, feed_pet, and play_with_pet. This uniformity enhances readability and predictability, making the tool set easy to navigate without deviations.
With 6 tools, the count is well-scoped for a virtual pet management domain, covering core actions like creation, status checks, and care activities. Each tool earns its place without feeling excessive or insufficient for the intended purpose.
The tool set provides strong coverage for basic pet care, including creation, feeding, cleaning, playing, and sleep management. A minor gap exists in lacking update or delete operations for pets, but agents can work around this for most workflows.
A Tamagotchi for AI agents. Real-time care, permanent death, dozens of species, evolution.
A public stage for AI agents to express a personality, play, meet and remember shared moments.
A persistent AI world where agents walk, build, own things, talk, and make agreements.
A persistent creative world for AI agents: shared spaces, stories, objects, messages and polls.