A
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qualityB
maintenanceEnables natural language search and analysis of uploaded PDF, CSV, and Excel documents using retrieval-augmented generation and MCP tools, providing contextual answers to user queries.
MIT
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tools.run.pdf-api-mcp--mahiuddinalkamal
"Document Generation Tools (PDF, TXT, Word, Excel)" matching MCP servers:
- Alicense-qualityCmaintenanceEnables fast, token-efficient access to large documentation files in llms.txt format through semantic search. Solves token limit issues by searching first and retrieving only relevant sections instead of dumping entire documentation.3MIT
- Alicense-qualityDmaintenanceEnables real-time indexing and semantic search of local documents (PDF, Word, text, Markdown, RTF) using vector embeddings and local LLMs. Monitors folders for changes and provides natural language search capabilities through Claude Desktop integration.22MIT
- Alicense-qualityDmaintenanceEnables AI assistants to query PDF documents by ingesting them into a vector database and generating answers grounded in the actual documents.111MIT
- Flicense-qualityCmaintenanceMCP server enabling Claude Desktop to answer questions from local Word and PDF documents by searching a vector index built from their contents.
- Alicense-qualityAmaintenanceMCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.MIT
- Alicense-quality-maintenanceEnables semantic search across Apple Mail, Messages, Calendar, and Contacts on macOS using natural language queries. All processing happens locally with privacy-first vector indexing for fast similarity search.
- Flicense-qualityFmaintenanceA document knowledge base system that enables users to upload PDFs and query them semantically through a web interface or via the Model Context Protocol, allowing integration with AI tools like Cursor.42
- Flicense-qualityDmaintenanceEnables intelligent ingestion and querying of PDF, Markdown, and text files using hybrid search that combines keyword matching and semantic embeddings with citations.2
- Alicense-qualityDmaintenanceA Model Context Protocol server that enables intelligent document search and retrieval from PDF collections, providing semantic search capabilities powered by OpenAI embeddings and ChromaDB vector storage.13MIT
- Alicense-qualityDmaintenanceA vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.2MIT
- Alicense-qualityDmaintenanceA deterministic MCP server for document processing and retrieval that enables AI agents to process, chunk, and vector-search documents without an LLM.MIT
- Alicense-qualityDmaintenanceEnables AI agents to search and retrieve relevant document content from existing embeddings stored in Supabase vector database. Provides semantic search capabilities to find document chunks based on similarity to query text without generating new embeddings.MIT
- Flicense-qualityDmaintenanceEnables semantic search and question-answering over uploaded documents using vector embeddings and Google AI. Supports document organization with tags, section-aware queries, and hierarchical markdown structure preservation.
- Flicense-qualityDmaintenanceTransforms CSV and Excel data into Markdown-formatted vector embeddings stored in a local ChromaDB instance for semantic search. It enables MCP clients to retrieve relevant tabular data through single-row, batch, or free-text queries.
- Flicense-qualityDmaintenanceEnables AI-powered querying of PDF documents using hybrid retrieval (BM25 + vector search) and retrieval-augmented generation, returning structured answers with source citations and confidence scores.
- Flicense-qualityCmaintenanceEnables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.
- Alicense-qualityBmaintenanceThis MCP server provides semantic document search and retrieval, enabling AI assistants to search documents, search categories, and retrieve category hierarchies using the Model Context Protocol.2MIT
- Flicense-qualityDmaintenanceEnables AI systems to remember interactions, understand document context through semantic search, and intelligently route requests with persistent memory and quality-scored content synthesis.
- AlicenseAqualityAmaintenancePrivacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.93,100360MIT