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Copy-Paste MCP

by ananddtyagi
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TypeScript

コピー＆ペーストMCP

テキスト コンテンツから特定の行を抽出するためのツールを提供するモデル コンテキスト プロトコル (MCP) サーバー。

特徴

  • 任意のテキストコンテンツから特定の行範囲を抽出するシンプルなツール

  • コンテンツのフォーマットと改行を正確に保持します

  • 内容の変更なし - 純粋な抽出

  • AIツールとの容易な統合を可能にするMCPサーバーの実装

Related MCP server: MCP PDF Reader

MCPサーバー

このパッケージには、Claude Desktop、VS Code、その他の MCP 互換アプリケーションなどの MCP クライアントで使用できるツールとして行抽出機能を公開する MCP サーバーが含まれています。

利用可能なツール

  1. extract-lines - テキストコンテンツから特定の範囲の行を抽出します

インストール

  1. リポジトリをクローンする

  2. 依存関係をインストールします:

npm install

使用法

MCPサーバーの起動

npm start

これにより、MCP クライアントが接続できる stdio トランスポートを使用して MCP サーバーが起動します。

サーバーへの接続

MCP 互換クライアント (Claude Desktop など) では、次のコマンドでこのサーバーを追加できます。

  • 名前: コピー＆ペースト

  • コマンド: node /path/to/copy-paste-mcp/dist/index.js

  • トランスポート: stdio

ツールの使用

接続すると、MCP クライアントのインターフェースを通じてツールを使用できるようになります。

行の抽出

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

これにより、提供されたテキスト コンテンツの最初の 2 行が返されます。

例

大きなテキスト ブロックから 10 行目から 20 行目を抽出します。

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

1 行だけ抽出します (行 5):

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

なぜこれを使うのですか?

このツールは、次のことが必要な場合に役立ちます。

  • 大きなテキストブロックから特定のセクションを抽出する

  • コードまたはドキュメントから正確な行範囲をコピーする

  • 変更を加えることなく正確なコンテンツ抽出を実現

  • MCPを介してライン抽出機能をAIワークフローに統合

  • 大きな文書の特定の部分を操作する

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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