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 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 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 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 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.
Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.
Provides access to Canadian federal parliamentary data (debates, bills, MPs, votes, Hansard transcripts) and legal information (case law and legislation through CanLII) for research and analysis.
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.
This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.
Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.