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MCP Excel Reader

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MCP Excel 阅读器

铁匠徽章一个模型上下文协议 (MCP) 服务器，用于读取 Excel 文件，并支持自动分块和分页。该工具基于 SheetJS 和 TypeScript 构建，可自动将大型 Excel 文件拆分为易于管理的块，从而帮助您高效地处理这些文件。

特征

  • 📊 读取具有自动大小限制的 Excel 文件（.xlsx、.xls）

  • 🔄 大型数据集的自动分块

  • 📑 工作表选择和行分页

  • 📅 正确的日期处理

  • ⚡ 针对大文件进行了优化

  • 🛡️ 错误处理和验证

Related MCP server: Excel MCP Server

安装

通过 Smithery 安装

要通过Smithery自动为 Claude Desktop 安装 Excel Reader：

npx -y @smithery/cli install @ArchimedesCrypto/excel-reader-mcp-chunked --client claude

作为 MCP 服务器

  1. 全局安装：

npm install -g @archimdescrypto/excel-reader

  1. 添加到您的 MCP 设置文件（通常在~/.config/claude/settings.json或同等位置）：

{
  "mcpServers": {
    "excel-reader": {
      "command": "excel-reader",
      "env": {}
    }
  }
}

为了发展

  1. 克隆存储库：

git clone https://github.com/ArchimdesCrypto/mcp-excel-reader.git
cd mcp-excel-reader

  1. 安装依赖项：

npm install

  1. 构建项目：

npm run build

用法

用法

Excel 阅读器提供了一个单独的工具read_excel ，其参数如下：

interface ReadExcelArgs {
  filePath: string;      // Path to Excel file
  sheetName?: string;    // Optional sheet name (defaults to first sheet)
  startRow?: number;     // Optional starting row for pagination
  maxRows?: number;      // Optional maximum rows to read
}

// Response format
interface ExcelResponse {
  fileName: string;
  totalSheets: number;
  currentSheet: {
    name: string;
    totalRows: number;
    totalColumns: number;
    chunk: {
      rowStart: number;
      rowEnd: number;
      columns: string[];
      data: Record<string, any>[];
    };
    hasMore: boolean;
    nextChunk?: {
      rowStart: number;
      columns: string[];
    };
  };
}

基本用法

与 Claude 或其他 MCP 兼容 AI 一起使用时：

Read the Excel file at path/to/file.xlsx

人工智能将使用该工具读取文件，自动处理大文件的分块。

特征

  1. 自动分块

    • 自动将大文件分割成可管理的块

    • 默认块大小为 100KB

    • 提供分页元数据

  2. 工作表选择

    • 按名称阅读特定工作表

    • 如果未指定，则默认为第一张表

  3. 行分页

    • 使用 startRow 和 maxRows 控制要读取哪些行

    • 获取下一个块信息以进行连续读取

  4. 错误处理

    • 验证文件存在和格式

    • 提供清晰的错误信息

    • 优雅地处理格式错误的 Excel 文件

使用 SheetJS 功能进行扩展

Excel 阅读器基于 SheetJS 构建，并可通过其强大的功能进行扩展：

可用扩展

  1. 公式处理

    // Enable formula parsing
const wb = XLSX.read(data, {
  cellFormula: true,
  cellNF: true
});

  2. 单元格格式

    // Access cell styles and formatting
const styles = Object.keys(worksheet)
  .filter(key => key[0] !== '!')
  .map(key => ({
    cell: key,
    style: worksheet[key].s
  }));

  3. 数据验证

    // Access data validation rules
const validation = worksheet['!dataValidation'];

  4. 图纸特征

    • 合并单元格： worksheet['!merges']

    • 隐藏行/列： worksheet['!rows'] ， worksheet['!cols']

    • 工作表保护： worksheet['!protect']

有关更多功能和详细文档，请访问SheetJS 文档。

贡献

  1. 分叉存储库

  2. 创建你的功能分支（ git checkout -b feature/amazing-feature ）

  3. 提交您的更改（ git commit -m 'Add some amazing feature' ）

  4. 推送到分支（ git push origin feature/amazing-feature ）

  5. 打开拉取请求

执照

该项目根据 MIT 许可证获得许可 - 有关详细信息，请参阅LICENSE文件。

致谢

Available Tools

1 tool
read_excelB

Read an Excel file and return its contents as structured data

ParametersJSON Schema
NameRequiredDescriptionDefault
filePathYesPath to the Excel file to read
sheetNameNoName of the sheet to read (optional)
startRowNoStarting row index (optional)
maxRowsNoMaximum number of rows to read (optional)

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 reading and returning data, implying a read-only operation, but fails to address critical aspects like error handling (e.g., what happens if the file doesn't exist or is corrupted), performance considerations, or format specifics of the returned structured data.

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 that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded with the core functionality.

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?

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits and output format, which are important for a data-reading tool without structured output documentation.

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%, so the input schema already documents all parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as examples or usage tips for the parameters, meeting the baseline for high schema coverage.

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 verb ('Read') and resource ('an Excel file') with the outcome ('return its contents as structured data'). It's specific about what the tool does, but since there are no sibling tools mentioned, it cannot demonstrate differentiation from alternatives.

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 exclusions. It simply states what the tool does without context for usage decisions.

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 observedread_excel
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 ambiguity or overlap between tools. The single tool 'read_excel' has a clear and distinct purpose that cannot be confused with any other tool in the set.

Naming Consistency5/5

The single tool name 'read_excel' follows a clear verb_noun pattern. Since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions to evaluate.

Tool Count2/5

A single tool is generally too few for a server named 'MCP Excel Reader', as it suggests a limited scope that may not support typical Excel-related workflows like writing, updating, or querying data. This feels thin for the apparent domain.

Completeness2/5

The tool surface is severely incomplete for an Excel reader domain. While reading is covered, there are significant gaps such as writing, editing, formatting, or analyzing Excel files, which will likely cause agent failures in broader tasks.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

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