Enables local document question-answering and retrieval via MCP, supporting multi-turn conversation, intent recognition, and tools for document search, Q&A, and summarization.
Enables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.
An MCP-based AI agent that retrieves and processes documents to answer queries using a RAG pipeline with LangChain and Claude models. It enables document indexing, context-aware retrieval, and multi-tool orchestration for research and knowledgebase applications.
Enables 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.