MCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.
An MCP-native agentic platform orchestrating planner/executor/critic agents over hybrid RAG with three-tier memory, budget enforcement, safety guardrails, and full observability. It exposes all capabilities as MCP tools, enabling natural-language control of document ingestion, retrieval-augmented generation, and multi-step AI workflows.
A production-minded RAG service for MCP that answers questions over your documents with hybrid retrieval, PII redaction, and source citations, packaged for Docker/Kubernetes.
Hybrid RAG pipeline that indexes documents and exposes them via an MCP server, enabling natural language queries to retrieve relevant context chunks for LLMs.
A pluggable, observable modular RAG service framework that exposes tools via MCP protocol for AI assistants, supporting hybrid search, reranking, multi-modal processing, and evaluation.