"Generate Word documents" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Your private knowledge base: upload documents (.md, .txt, .docx, PDF, images), the platform indexes
Generate 18 AI readiness files (llms.txt, ai.txt, RAG indexes, schema) for any website.
- docs2mcpOAuthcom.docs2mcp
Query your own PDFs and documents from any MCP client. Every answer cites the page it came from.
Search 18M+ legal documents across 110+ countries. Case law, legislation, and doctrine with semantic + keyword hybrid search. Supports tool discovery, multi-jurisdictional queries, citation resolution, and full document retrieval. Requested missing datasets can be fully indexed within 48h.
Turn documents into structured, AI-ready data by parsing, enriching, chunking, and embedding.
Parse PDF/Word/PPT/HTML to Markdown; tables as JSON, image extraction, RAG chunking, page ranges.
Provide real-time data querying and visualization by integrating Tako with your agents. Generate o…
PDF, Word, PowerPoint, Excel, HTML, EPUB to Markdown: OCR, page ranges, tables, RAG chunking
AI-native art catalogue. Catalogue works, parse provenance, and generate signed RAIs.
Query Klaaro datasets, documents, and extracted records from any agent.
Vector RAG store for Word/Excel/PDF/PowerPoint. Break-even pricing, $5 per 5,700 pages.
Analyze job listings against your resume, track applications, and generate cover letters.
AI-powered RFP response management. Search Q&A libraries, draft responses, and upload documents.
The CustomGPT.ai MCP server is a fully managed, RAG-powered endpoint that connects large language models with private knowledge bases and external data sources. It provides tools for retrieval-augmented generation queries (send_message), data ingestion (upload_file), and source listing, enabling AI agents to query private documents like PDFs with high accuracy and real-time citations.
The Needle MCP server enables semantic search on documents stored in files like PDFs, DOCX, and XLSX by connecting AI applications to external data sources. It provides capabilities to create and manage document collections, perform natural language searches on stored content, and retrieve relevant information without requiring exact keyword matches.
Ingest, manage, and retrieve documents for RAG-powered AI applications
