MCP Excel Reader
Lector de Excel MCP
Un servidor de Protocolo de Contexto de Modelo (MCP) para leer archivos de Excel con fragmentación y paginación automáticas. Desarrollada con SheetJS y TypeScript, esta herramienta le ayuda a gestionar archivos grandes de Excel de forma eficiente, dividiéndolos automáticamente en fragmentos manejables.
Características
📊 Leer archivos Excel (.xlsx, .xls) con límites de tamaño automáticos
🔄 Fragmentación automática para grandes conjuntos de datos
📑 Selección de hojas y paginación de filas
📅 Manejo adecuado de fechas
⚡ Optimizado para archivos grandes
🛡️ Manejo de errores y validación
Related MCP server: Excel MCP Server
Instalación
Instalación mediante herrería
Para instalar Excel Reader para Claude Desktop automáticamente a través de Smithery :
npx -y @smithery/cli install @ArchimedesCrypto/excel-reader-mcp-chunked --client claudeComo servidor MCP
Instalar globalmente:
npm install -g @archimdescrypto/excel-readerAgregue a su archivo de configuración de MCP (generalmente en
~/.config/claude/settings.jsono equivalente):
{
"mcpServers": {
"excel-reader": {
"command": "excel-reader",
"env": {}
}
}
}Para el desarrollo
Clonar el repositorio:
git clone https://github.com/ArchimdesCrypto/mcp-excel-reader.git
cd mcp-excel-readerInstalar dependencias:
npm installConstruir el proyecto:
npm run buildUso
Uso
El lector de Excel proporciona una única herramienta read_excel con los siguientes parámetros:
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[];
};
};
}Uso básico
Cuando se utiliza con Claude u otra IA compatible con MCP:
Read the Excel file at path/to/file.xlsxLa IA utilizará la herramienta para leer el archivo y gestionará automáticamente la fragmentación de archivos grandes.
Características
Fragmentación automática
Divide automáticamente archivos grandes en fragmentos manejables
Tamaño de fragmento predeterminado de 100 KB
Proporciona metadatos para la paginación.
Selección de hojas
Leer hojas específicas por nombre
El valor predeterminado es la primera hoja si no se especifica
Paginación por filas
Controle qué filas leer con startRow y maxRows
Obtenga información del siguiente fragmento para una lectura continua
Manejo de errores
Valida la existencia y el formato del archivo.
Proporciona mensajes de error claros
Maneja archivos de Excel malformados con elegancia
Ampliación con funciones de SheetJS
El lector de Excel está basado en SheetJS y se puede ampliar con sus potentes funciones:
Extensiones disponibles
Manejo de fórmulas
// Enable formula parsing const wb = XLSX.read(data, { cellFormula: true, cellNF: true });Formato de celda
// Access cell styles and formatting const styles = Object.keys(worksheet) .filter(key => key[0] !== '!') .map(key => ({ cell: key, style: worksheet[key].s }));Validación de datos
// Access data validation rules const validation = worksheet['!dataValidation'];Características de la hoja
Celdas fusionadas:
worksheet['!merges']Filas/columnas ocultas:
worksheet['!rows'],worksheet['!cols']Protección de hoja:
worksheet['!protect']
Para conocer más funciones y documentación detallada, visita la Documentación de SheetJS .
Contribuyendo
Bifurcar el repositorio
Crea tu rama de funciones (
git checkout -b feature/amazing-feature)Confirme sus cambios (
git commit -m 'Add some amazing feature')Empujar a la rama (
git push origin feature/amazing-feature)Abrir una solicitud de extracción
Licencia
Este proyecto está licenciado bajo la licencia MIT: consulte el archivo de LICENCIA para obtener más detalles.
Expresiones de gratitud
Creado con SheetJS
Parte del ecosistema del Protocolo de Contexto Modelo
Available Tools
1 toolread_excelB
Read an Excel file and return its contents as structured data
| Name | Required | Description | Default |
|---|---|---|---|
| filePath | Yes | Path to the Excel file to read | |
| sheetName | No | Name of the sheet to read (optional) | |
| startRow | No | Starting row index (optional) | |
| maxRows | No | Maximum number of rows to read (optional) |
TDQS
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.
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.
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.
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.
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.
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 tool update
- First observed
read_excel
TDQS
Scored across 1 tool
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.
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.
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.
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.
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