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Copy-Paste MCP

by ananddtyagi
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TypeScript

복사-붙여넣기 MCP

텍스트 콘텐츠에서 특정 줄을 추출하는 도구를 제공하는 MCP(Model Context Protocol) 서버입니다.

특징

  • 모든 텍스트 콘텐츠에서 특정 줄 범위를 추출하는 간단한 도구

  • 정확한 콘텐츠 형식과 줄 바꿈을 유지합니다.

  • 내용 수정 없음 - 순수 추출

  • AI 도구와의 쉬운 통합을 위한 MCP 서버 구현

Related MCP server: MCP PDF Reader

MCP 서버

이 패키지에는 Claude Desktop, VS Code 또는 기타 MCP 호환 애플리케이션과 같은 모든 MCP 클라이언트에서 사용할 수 있는 도구로 줄 추출 기능을 제공하는 MCP 서버가 포함되어 있습니다.

사용 가능한 도구

  1. extract-lines - 텍스트 콘텐츠에서 특정 범위의 줄을 추출합니다.

설치

  1. 저장소를 복제합니다

  2. 종속성 설치:

지엑스피1

용법

MCP 서버 시작

npm start

이렇게 하면 MCP 클라이언트가 연결할 수 있는 stdio 전송을 사용하여 MCP 서버가 시작됩니다.

서버에 연결

MCP 호환 클라이언트(예: Claude Desktop)에서는 다음을 사용하여 이 서버를 추가할 수 있습니다.

  • 이름: 복사-붙여넣기

  • 명령어: node /path/to/copy-paste-mcp/dist/index.js

  • 전송: stdio

도구 사용

연결되면 MCP 클라이언트 인터페이스를 통해 도구를 사용할 수 있습니다.

줄 추출

Tool: extract-lines
Parameters:
  - text: "Your multi-line text content goes here\nSecond line\nThird line"
  - start_line: 1
  - end_line: 2

제공된 텍스트 콘텐츠의 처음 두 줄이 반환됩니다.

예시

큰 텍스트 블록에서 10~20번째 줄을 추출합니다.

Tool: extract-lines
Parameters:
  - text: [your text content with many lines]
  - start_line: 10
  - end_line: 20

단 한 줄만 추출합니다(5번째 줄):

Tool: extract-lines
Parameters:
  - text: [your text content]
  - start_line: 5
  - end_line: 5

왜 이것을 사용해야 하나요?

이 도구는 다음과 같은 경우에 유용합니다.

  • 큰 텍스트 블록에서 특정 섹션 추출

  • 코드나 문서에서 정확한 줄 범위를 복사합니다.

  • 어떠한 변경 없이 정확한 콘텐츠 추출을 보장합니다.

  • MCP를 통해 AI 워크플로에 라인 추출 기능 통합

  • 대용량 문서의 특정 부분 작업

Available Tools

1 tool
extract-linesB

Extract a specific range of lines from text content

ParametersJSON Schema
NameRequiredDescriptionDefault
textYesThe full text content to extract lines from
start_lineYesStarting line number (inclusive)
end_lineYesEnding line number (inclusive)

TDQS

B3.1/5.0
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 mentions the extraction action but doesn't describe what happens with invalid inputs (e.g., start_line > end_line), whether the operation is read-only or has side effects, error handling, or output format. This leaves significant behavioral gaps for an agent.

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 with zero wasted words. It's appropriately sized for this simple tool and front-loads the core functionality clearly.

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?

For a simple text processing tool with no annotations, no output schema, and 100% schema coverage, the description is minimally adequate. It covers the basic purpose but lacks behavioral details and usage context that would help an agent use it correctly in practice.

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 all three parameters well-documented in the schema. The description adds no additional parameter semantics beyond implying a range operation. This meets the baseline of 3 when the schema does the heavy lifting.

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 ('extract') and resource ('lines from text content'), and specifies the scope ('a specific range'). It doesn't need sibling differentiation since there are no sibling tools. However, it could be slightly more specific about what 'extract' means operationally.

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, prerequisites, or constraints. It simply states what the tool does without context about appropriate use cases or limitations.

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 update
    • First observedextract-lines
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.2/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap with other tools, making disambiguation perfect.

Naming Consistency5/5

The single tool uses a clear verb_noun pattern (extract-lines), and with no other tools to compare, consistency is inherently perfect.

Tool Count2/5

One tool is too few for a server named 'Copy-Paste MCP', which suggests broader copy-paste functionality, making the scope feel incomplete and thin.

Completeness2/5

The tool only extracts lines from text, lacking obvious operations like copying full text, pasting, or handling other copy-paste tasks, indicating significant gaps for the domain.

Maintenance

ActivityInactive
ResponsivenessNo issues

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