Enables autonomous orchestration of vector search, knowledge graph queries, and web crawling through a single MCP interface, providing agentic RAG capabilities for AI assistants.
Enables a unified AI assistant that combines document retrieval (RAG), database queries via MCP tools, and web search, allowing users to ask complex questions and receive answers from multiple enterprise sources.
Enables AI agents to securely query PostgreSQL with pgvector, DynamoDB, and MongoDB Atlas with Vector Search through a read-only, allowlisted MCP interface.
Enables enterprise AI agents to query governed data lineage, PII-aware schema documentation, and semantic metadata from SQL logs via MCP, with role-based access and vector search.