Provides a unified context layer for AI agents, enabling ranked search, file management, context bundles, database queries, and connected source access through MCP, all scoped to organizational permissions with citations.
A governed context layer for internal data exposed over MCP, enabling agents to query governed definitions, retrieve grounded data, and execute scoped actions with citations and auditing.
Enables LLM agents to query a structured knowledge library for search, explanations, related concepts, learning paths, examples, and cross-domain references via MCP.
Enables querying context about the MAM product components and architecture through MCP, allowing agents to retrieve targeted product information on demand instead of loading full documentation.
Enables MCP clients to serve and query semantic models, providing tools for entity descriptions, metric lookups, context resolution, and operation validation for AI agents.
Governed knowledge base for AI agents via the Model Context Protocol (MCP), enabling agents to search, read, and contribute persisted knowledge with versioning, audit trails, and approval workflows.
