"excel" matching MCP servers:

Enables reading and writing Excel workbooks (.xlsx) through MCP. Supports listing sheets, tables, pivot tables, reading cell data, exporting to CSV/text/Markdown, and creating/modifying Excel files.

Enables AI clients to read, write, and manage Excel workbooks (.xlsx/.xlsm) directly via openpyxl, with comprehensive tools for data, formatting, formulas, charts, and more.

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

Enables normalizing arbitrary Excel spreadsheets with varied headers into 19 canonical fields and clean JSON, with optional LLM disambiguation and offline fallback. Exposes MCP tools for use in Claude, Cursor, and Windsurf.

Enables querying Excel and CSV files using SQL via natural language, allowing AI assistants to analyze data without manual SQL writing.

An MCP server that allows LLMs to read, analyze, and interact with Excel files through file operations, data discovery, and comprehensive analysis tools.

Generates formatted Excel (.xlsx) files from user requests and deposits them into Cleyrop project data.

A Model Context Protocol server that enables AI assistants to read from and write to Microsoft Excel files, supporting formats like xlsx, xlsm, xltx, and xltm.

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 LLMs to work with Excel and CSV files through structured tools for workbook operations, formatting, charts, ETL, analysis, and more.

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files, enabling extraction of data from entire workbooks or specific sheets with results returned in structured JSON format.

Provides efficient handling of large Excel files through automatic chunking and pagination, using MCP to enable seamless file reading and management features such as sheet selection and error handling.

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.

An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.

Enables AI agents to read, write, analyze, and transform Excel spreadsheets (.xlsx) through the Model Context Protocol.

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.

Parses WeChat order messages, merges follow-up updates, and writes structured orders into a OneDrive Excel workbook through Microsoft Graph.

A Model Context Protocol server that enables AI agents to create, read, and modify Excel workbooks without requiring Microsoft Excel installation.

Enables AI agents to operate Excel files through standardized MCP interfaces, including merging, splitting by column, and exporting multi-sheet workbooks.

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 collecting data from configurable sources such as Jira, SonarQube, Uptime Robot, npm audit, and HTTP endpoints, then exporting it to an Excel file with one sheet per source.

Enables high-performance read/write operations, reconciliation, formula recalculation, pivot refresh, macro execution, and PDF export for spreadsheet workbooks on Windows.

Enables users to analyze local Excel and CSV files through natural language queries and a web dashboard while keeping data local. It supports saving specific analyses as reusable tools and building a custom analytics toolkit within Claude Desktop.

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

The Excel to JSON MCP provides a standardized interface for converting Excel and CSV data into JSON format using the Model Context Protocol.

The JSON to Excel MCP provides a standardized interface for converting (1)JSON data (2)URL pointing to JSON files into CSV format

Fast, multi-sheet Excel retrieval and writing via MCP, supporting efficient data access with patch-based navigation and formula support.

Local-first data quality validation for Excel/CSV: schema-aware checks with 10 zero-code constraint types (uniqueness, ranges, foreign keys and more) and row-level error reports.

Enables AI assistants to convert German PDF invoices into XRechnung 3.0 and ZUGFeRD e-invoices with KoSIT validation and missing-field prompts, and Brazilian bank statement PDFs into OFX, CSV, and Excel after balance validation.

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.

MCP server that exposes local Python scripts as tools for AI clients (e.g. Claude Desktop), enabling directory tree generation, Excel-to-text conversion, Python code extraction, and text file merging.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

Enables creating and deploying KoboToolbox XLSForm questionnaires, managing data collection, analyzing submissions, and generating Excel, Word, and PDF deliverables directly from a Claude conversation.

Enables AI agents to work with a real Excel-compatible spreadsheet engine, allowing them to create and manipulate structured data blocks, write and evaluate formulas, and save genuine .xlsx files with live formulas for human verification and reuse.

Enables MCP clients to extract tables and text from digital PDF invoices, bank statements, and bills into CSV, JSON, or Excel, with automatic PII redaction by default.

Enables accountants and bookkeepers to ask practice-wide questions across every connected client Xero organisation in one read-only view — overdue invoices, payroll shortfalls, client health scores, trending-trouble lists and practice totals such as revenue and average DSO. It also generates ready-to-send Excel month-end packs per client, with every reported figure accompanied by the rule or formula that produced it and no financial data persisted to disk.

Imports CSV or Excel files into Dynamics 365 Finance & Operations data projects through the Data Management Framework, generating manifests, resolving entity targets and dependency order, and waiting for execution results. Also exports data projects and exposes tools to search the entity catalogue, inspect entity fields, and check execution status.

Provides secure, agentic Excel analysis and calculation capabilities, enabling users to inspect workbook structure, perform statistical computations, write formulas, and generate outputs through whitelisted MCP tools with audit trails and backups.

Enables AI agents to safely ingest, inspect, edit, and export manufacturing documents (Excel, PDF, Word, Markdown) with controlled patch workflows and MES entity extraction.

MCP server for reading and writing data files (Excel, PDF, CSV, JSON, text) with safe write rules and provenance tracking.