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"excel" matching MCP servers:

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    Enables querying Excel and CSV files using SQL via natural language, allowing AI assistants to analyze data without manual SQL writing.
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    MIT
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    Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
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    MIT
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    Offline AI-powered local file search MCP server for Windows. Searches inside document contents (Word, Excel, PDF, PowerPoint, HWP) using BM25 + dense vector hybrid search. 100% local, no cloud, no login, no telemetry.
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    Apache 2.0
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    Ad libraries are public but fragmented. Every platform is a silo - different UI, different filters, different quirks. If you want to see what competitors are running, you're either opening four tabs and pasting into Excel, or maintaining scrapers that rot with every layout change. adextract gives AI agents a single MCP endpoint to search, read, and compare ads across Meta, TikTok, LinkedIn, and mo
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    MIT
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    Upload documents (Word, Excel, PDF, PowerPoint) to a vector RAG store and perform semantic search with page-level citations. Queries are free; ingestion costs credits at break-even pricing.
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    MIT
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    MCP server for indexing, semantic search, and generation of multi-format documents. Exposes 13 tools over JSON-RPC 2.0 so an LLM can search your local PDF, Excel, and Word files, and create or edit Excel and Word documents.
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    AGPL 3.0
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    Imagine you could hand Claude a filing cabinet of your documents and say "remember all of this." Later you just ask questions, and Claude answers from what it remembers — citing which document each fact came from. That's Memorised them All. It's a small add-on (an MCP server) for Claude Desktop and Claude Code that: Reads your files — PDFs, Word/Excel/PowerPoint, web pages, images (with OCR), ev
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    MIT
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    AI-native data analysis agent as an MCP Server. Connect your Excel files, CSVs, and MySQL databases. Understand business semantics. Query with natural language.
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    MIT
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    Enables AI assistants to parse and search documents including PDF, Word, Excel, PowerPoint, and images via OCR, with support for semantic search and batch processing.
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    MIT
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    Enables users to ask questions about their spreadsheets in plain English and receive instant answers using DuckDB-powered analytics, supporting multiple file formats like Excel, CSV, and Parquet.
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    MIT
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    Enables intelligent file searching in local directories using natural language queries. Supports searching by file type, filename patterns, and content across multiple formats including PDF, Word, Excel, and text files with AI-powered relevance scoring.
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  • F
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    Retrieval-augmented MCP server for company project documents (Markdown, Word, Excel, PDF) with vector search, offline embedding, and token-based project authorization.
    Last updated