Serve your agents fresh data at Redis speed.
Redis Context Retriever
Turn live business data into agent-ready tools so AI apps can retrieve the right facts fast.
Agent-native support for MCP and CLI
Context Retriever is designed for AI agents to operate directly, using MCP to connect to tools and a CLI for execution and automation.
Rich semantic definitions
Get deeper understanding with structured context that captures meaning, relationships, and intent instead of just raw data.
Designed for data security
Manage access with generated tools and MCP, not broad raw database access. Build agents that retrieve governed context without exposing production systems to open-ended queries.
Why Context Retriever
Schema-first semantic layer
Model entities, fields, and relationships so agents understand how business data connects.
Generated MCP tools
Turn data schemas into governed tools agents can call at runtime.
Entity navigation
Help agents move across customers, orders, tickets, claims, and transactions without guessing across disconnected endpoints.
Controlled data access
Expose approved context paths through tools, not broad raw database access.
Runtime retrieval
Retrieve live operational context during each agent step so answers reflect current business state.
Redis Iris-ready
Pair with Redis Data Integration, Redis Search, LangCache, and Redis Agent Memory for fresh, fast, compounding context.