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ArchimedesCrypto

MCP Excel Reader

by ArchimedesCrypto
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TypeScript
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MCP Excel Reader

A Model Context Protocol (MCP) server for reading Excel files with automatic chunking and pagination support. Built with SheetJS and TypeScript, this tool helps you handle large Excel files efficiently by automatically breaking them into manageable chunks.

Features

  • ๐Ÿ“Š Read Excel files (.xlsx, .xls) with automatic size limits

  • ๐Ÿ”„ Automatic chunking for large datasets

  • ๐Ÿ“‘ Sheet selection and row pagination

  • ๐Ÿ“… Proper date handling

  • โšก Optimized for large files

  • ๐Ÿ›ก๏ธ Error handling and validation

Related MCP server: Excel MCP Server

Installation

Installing via Smithery

To install Excel Reader for Claude Desktop automatically via Smithery:

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

As an MCP Server

  1. Install globally:

npm install -g @archimdescrypto/excel-reader

  1. Add to your MCP settings file (usually at ~/.config/claude/settings.json or equivalent):

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

For Development

  1. Clone the repository:

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

  1. Install dependencies:

npm install

  1. Build the project:

npm run build

Usage

Usage

The Excel Reader provides a single tool read_excel with the following parameters:

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[];
    };
  };
}

Basic Usage

When used with Claude or another MCP-compatible AI:

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

The AI will use the tool to read the file, automatically handling chunking for large files.

Features

  1. Automatic Chunking

    • Automatically splits large files into manageable chunks

    • Default chunk size of 100KB

    • Provides metadata for pagination

  2. Sheet Selection

    • Read specific sheets by name

    • Defaults to first sheet if not specified

  3. Row Pagination

    • Control which rows to read with startRow and maxRows

    • Get next chunk information for continuous reading

  4. Error Handling

    • Validates file existence and format

    • Provides clear error messages

    • Handles malformed Excel files gracefully

Extending with SheetJS Features

The Excel Reader is built on SheetJS and can be extended with its powerful features:

Available Extensions

  1. Formula Handling

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

  2. Cell Formatting

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

  3. Data Validation

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

  4. Sheet Features

    • Merged Cells: worksheet['!merges']

    • Hidden Rows/Columns: worksheet['!rows'], worksheet['!cols']

    • Sheet Protection: worksheet['!protect']

For more features and detailed documentation, visit the SheetJS Documentation.

Contributing

  1. Fork the repository

  2. Create your feature branch (git checkout -b feature/amazing-feature)

  3. Commit your changes (git commit -m 'Add some amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

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. Dates show when Glama detected each change.

  1. 1 tool update
    • First observedread_excel
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TDQS

B3.2/5.0
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
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

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  • xls-mcp-servers

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  • excel-tools-mcp

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