"Working with Excel or Excel tutorials" matching MCP servers:

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

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 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.

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 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.

Enables efficient reading, analyzing, and querying of Excel, CSV, and JSON files with support for chunked processing, column/field filtering, and streaming for large datasets. Supports multiple transport protocols (stdio, HTTP, SSE) for flexible integration.

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

MCP server for reading and inspecting local Excel files (.xlsx, .xlsm, .xls, .xlsb, .ods) with tools for inspecting metadata, reading ranges, and profiling structure.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Enables AI agents to operate DSpace repositories through a typed interface, including SAF package building, metadata editing, scientometric harvesting, open-access PDF downloads, and repository administration.

Custom MCP server for NotebookLM that adds audio source upload, YouTube source ingestion, source readiness polling, and transcript export, complementing standard Q&A and audio overview tools.

Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.

Enables AI agents to query free biomedical and pharmaceutical APIs for clinical trials, drug data, molecular structures, adverse events, and research literature.

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.

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 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.

An MCP server for college placement cells to analyze student profiles from bulk Excel data, search students, and access evidence-backed skill intelligence from resumes, GitHub, LeetCode, and portfolios. It provides tools for skill gap analysis and profile completeness evaluation.