"How to Read an Excel File" matching MCP servers:

Enables AI agents to read Excel files with full content extraction, including embedded images, cell data, formulas, and merged cells, returning multimodal content for vision-capable models.

An MCP server that provides comprehensive Excel file operations, data analysis, and visualization capabilities for working with various spreadsheet formats like XLSX, CSV, and JSON.

Enables conversational data analysis of Excel/CSV files through natural language queries, powered by 395 Excel functions via HyperFormula and multi-provider AI. Supports advanced analytics, bulk operations, financial modeling, and large file processing with intelligent chunking.

Enables AI models to search, read, and analyze Excel files from your local file system with support for multiple worksheets, text search, and JSON data conversion.

Enables AI agents to read real Excel files with messy layouts, auto-detecting header rows and handling merged cells to extract clean tabular data via MCP tools.

Enables AI agents to analyze Excel files through atomic operations like filtering, aggregation, and grouping without loading raw data into context.

Reads Excel files and returns each sheet's content as CSV text. Enables AI models to extract data from Excel spreadsheets via natural language.

Enables MCP clients to upload tabular datasets and run deterministic Pandas, NumPy, Excel/openpyxl, and automated EDA operations through registered tools.

Enables users to run DCF/NAV/CCA valuations, Fama-French 5-Factor cost of equity, KMV credit risk, derivatives pricing, and Excel/PDF/Word report review with IVS 2025, IFRS 13, and HKFRS 9 compliance.

Enables read-only SQL querying and exploration of data files (CSV, Parquet, JSON, Excel, etc.) via DuckDB, supporting local paths, globs, URLs, and S3 buckets.

Enables AI clients to analyze any company domain and determine its AI maturity tier (commercialized, deployed, declared, or none) with supporting evidence, via a single tool backed by an Apify actor.

Enables an LLM to search and research Goodreads books, ratings, and reviews using public data, without login or writes.

Enables AI agents to search and read PubMed academic literature directly, without requiring an NCBI API key.

Enables coding agents to query AI model API prices, including historical point-in-time lookups with cited sources, using a bundled dated dataset and requiring no API keys.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables searching live job postings, aggregating labour-market slices, and reporting how long listings have been open, with filters for titles, location, salary, and more.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

Gives AI agents read access to ads running across Meta platforms without an API key, returning full creatives, real landing URLs, and complete platform lists.

An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.

Enables read-only analysis of local unstructured documents by scanning a folder, extracting text and structural metadata, and passing content with truncation and error-awareness to an LLM for summarization.