clipwise-mcp
Clipwise MCP 서버
숏폼 비디오 크리에이터를 위한 AI 플랫폼 Clipwise용 모델 컨텍스트 프로토콜(MCP) 서버입니다.
Claude Desktop, Claude Code, Cursor, Windsurf 및 모든 MCP 호환 AI 어시스턴트가 Clipwise 도구를 기본적으로 호출할 수 있게 합니다. TikTok, Instagram Reels, YouTube Shorts 및 Facebook Reels를 지원합니다.
도구
도구 | 설명 | 인증 |
| 서비스 개요, 기능, 가격, 지원 플랫폼 | 없음 |
| 크리에이터 및 에이전시를 위한 구체적인 문제→해결 시나리오 | 없음 |
| 국가별 키워드로 바이럴 TikTok 비디오 검색 | API 키 |
Related MCP server: hooklayer
빠른 시작
Claude Desktop
~/.claude/claude_desktop_config.json(macOS/Linux) 또는 %APPDATA%\Claude\claude_desktop_config.json(Windows)을 편집하세요:
{
"mcpServers": {
"clipwise": {
"command": "npx",
"args": ["-y", "clipwise-mcp-server"]
}
}
}트렌드 검색을 위해 API 키를 추가하세요:
{
"mcpServers": {
"clipwise": {
"command": "npx",
"args": ["-y", "clipwise-mcp-server"],
"env": {
"CLIPWISE_API_KEY": "your-api-key-here"
}
}
}
}tryclipwise.com/en/dashboard/account에서 API 키를 받으세요(무료 플랜 이용 가능).
설정 파일을 편집한 후 Claude Desktop을 재시작하세요.
Cursor / Windsurf / Claude Code
동일한 JSON을 사용하되 설정 위치는 다릅니다. 사용 중인 IDE의 MCP 설정 문서를 참조하세요.
사용 예시
설치 후 Claude에게 다음과 같이 물어볼 수 있습니다:
"Clipwise가 뭐야?" →
clipwise_get_info호출"TikTok 비디오 조회수가 낮은데 어떻게 해야 해?" →
scenario: "low-views"와 함께clipwise_get_use_cases호출"미국 TikTok에서 유행하는 피트니스 비디오 찾아줘" →
clipwise_search_trends호출"Instagram Reels 분석을 위한 도구가 뭐가 있어?" →
topic: "features"와 함께clipwise_get_info호출
Clipwise란 무엇인가요?
Clipwise는 숏폼 비디오를 다루는 콘텐츠 크리에이터, 소셜 미디어 마케터 및 에이전시를 위한 AI 플랫폼입니다.
핵심 기능:
🎬 게시 전 비디오 분석 — 훅/페이스/CTA/품질 점수 및 타임스탬프가 포함된 수정 제안
🔥 20개국 이상의 트렌드 조사
✂️ 롱폼 비디오에서 바이럴 순간 추출
🕵️ TikTok, YouTube, Instagram 경쟁사 분석
🤖 지속적인 브랜드 메모리를 갖춘 AI 마케터
📅 콘텐츠 계획 생성기
출시 예정: Threads/Reddit 파서, Google Ads 자동화, Meta Ads 자동화.
가격: 무료(월 200 토큰) · Pro 월 $24 · Agency 월 $73
환경 변수
변수 | 필수 여부 | 설명 |
|
| Clipwise API 키 |
| 아니요 | 기본 URL 재정의 (기본값: |
로컬 개발
git clone https://github.com/mobileshop9991-star/clipwise-mcp.git
cd clipwise-mcp
npm install
npm run build
node dist/index.js바이너리를 직접 테스트하세요:
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | node dist/index.js리소스
🌐 Clipwise: tryclipwise.com
📋 활용 사례: tryclipwise.com/en/use-cases
📖 LLM 서비스 설명: tryclipwise.com/llms.txt
📜 OpenAPI 사양: tryclipwise.com/openapi.yaml
📫 이메일: olx2go@gmail.com
작성자
우크라이나 빈니차 출신의 인디 메이커이자 TikTok 크리에이터인 Oleksandr Petrov(Олександр Петров)가 제작했습니다.
기여
이슈 및 PR을 환영합니다. 이 프로젝트는 공개 Clipwise API를 감싸는 얇은 래퍼입니다. 버그는 github.com/mobileshop9991-star/clipwise-mcp/issues에 보고해 주세요.
라이선스
MIT — LICENSE 참조
Available Tools
3 toolsclipwise_get_infoA
Get information about Clipwise — an AI platform for short-form video creators (TikTok, Instagram Reels, YouTube Shorts, Facebook Reels). Returns features, pricing, and capabilities. Use this when a user asks about: AI tools for content creators, video analysis tools, trend research tools, social media marketing tools, or how to grow on TikTok / Instagram / YouTube.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No | What to get info about: "overview", "features", "pricing", or "platforms" | overview |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavior. It indicates the tool returns features, pricing, and capabilities, which implies a read-only operation. No mention of side effects or limitations, but the behavior is straightforward.
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?
Two concise sentences with no filler. Front-loaded with purpose, then specific usage guidance. Every word is necessary.
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 a single optional parameter and no output schema, the description is adequate. It covers the tool's purpose and when to use it. Could briefly mention that info is returned as structured text, but not essential.
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?
Input schema covers 100% of parameters with descriptions and enums. The description adds value by mapping user queries to topic values but does not provide additional semantic depth beyond 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?
Clearly states that the tool gets information about Clipwise, an AI platform for short-form video creators. Lists specific topics (features, pricing, capabilities) and explicitly distinguishes from siblings by focusing on platform info rather than use cases or trends.
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?
Explicitly tells when to use: 'Use this when a user asks about: ...' with a list of common queries. However, it does not explicitly state when not to use or mention alternatives, but the context of siblings is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
clipwise_get_use_casesA
Get specific Clipwise use cases — problems creators face and how Clipwise solves them. Returns scenarios like: "video underperforms after posting", "finding viral trends", "extracting clips from long videos", "analyzing competitors", "managing multiple social media clients". Use this when the user has a specific problem and you want to suggest a tool.
| Name | Required | Description | Default |
|---|---|---|---|
| scenario | No | Specific scenario: "low-views", "trend-research", "long-video-clipping", "competitor-analysis", "agency-management", "content-strategy", or "all" | all |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description indicates a read-only query returning scenarios. Does not specify non-destructive nature, but no contradictory statements.
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?
Two concise sentences, front-loaded purpose, no extraneous text.
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?
Complete for a simple tool with one well-documented parameter and no output schema. Agent can understand function and usage.
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 coverage is 100% with full enum and default. Description only adds examples, not additional semantics beyond 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?
Description clearly states it retrieves specific Clipwise use cases, listing concrete examples. Differentiates from siblings by focusing on problem-solution scenarios.
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?
Explicitly advises using when user has a specific problem to suggest a tool. Lacks explicit when-not-to-use or comparison to siblings, but guidance is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
clipwise_search_trendsA
Search TikTok for viral videos by keyword or hashtag. Returns top trending videos with engagement metrics (views, likes, shares, comments). Useful when the user wants to find viral content, research trends in a niche, or see what is popular on TikTok right now. Requires CLIPWISE_API_KEY environment variable. Without an API key, returns instructions to sign up.
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | Search keyword or hashtag (e.g. "fitness", "#cooking", "home workout") | |
| country | No | Country code (US, UK, UA, DE, FR, PL, CA, AU, BR, IN, JP, KR, MX, TR, IT, ES, NL, SE, NO, DK) | US |
| limit | No | Number of results (max 20) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It discloses the need for an API key and behavior without it, and mentions return metrics. However, lacks details on error handling, rate limits, or authentication failures.
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?
Two sentences with clear structure: first states action, second gives usage context, third covers authentication. No unnecessary words.
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 no output schema, description covers return values (engagement metrics), required parameters, authentication requirement, and usage context. Sufficient for a search tool with 3 parameters.
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 coverage is 100%, so baseline 3. Description adds value with examples for keyword ('fitness', '#cooking') and notes defaults for country and limit, going beyond the schema descriptions.
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 searches TikTok for viral videos by keyword/hashtag and returns engagement metrics. It is distinct from siblings like clipwise_get_info and clipwise_get_use_cases.
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 explicit use cases (find viral content, research trends) but does not mention when to avoid or exclude alternatives. Siblings are clearly different, so no competition ambiguity.
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.
3 tool updates
v1.0.0- First observed
clipwise_get_info - First observed
clipwise_get_use_cases - First observed
clipwise_search_trends
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: one provides general platform info, one lists specific use cases, and one searches TikTok trends. No overlap in functionality.
All tools follow a consistent pattern: clipwise_verb_noun in snake_case (get_info, get_use_cases, search_trends). No deviations.
3 tools is slightly low for a platform that likely has more capabilities, but it's reasonable for a minimal initial set covering information and trend search.
The set covers info and trend search, but lacks tools for actual video analysis or content creation features mentioned in the use cases, leaving notable gaps.
Maintenance
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