Semantic Search
Find code by meaning, not keywords. Ask questions in natural language and get accurate results across the entire codebase.
@-Mentions
Point the agent at files, folders, docs, the web, or git history. Precise context control for every conversation.
Privacy Controls
Org-wide privacy mode, file exclusions, and configurable data policies. Enterprise grade security for sensitive codebases.
Instant Re-indexing
Securely reuse a teammate's index so new developers get full codebase understanding in seconds, not hours.
Custom Embeddings
Purpose-built embedding model gives Cursor best-in-class recall across codebases of any size and complexity.
Web and Docs
Agent can search the web and reference configured documentation URLs, combining codebase knowledge with external context.
Project opened
Cursor detects the project and begins indexing files using the custom embedding model
Embeddings generated
Each file is converted into semantic vectors that capture meaning, structure, and relationships
Index stored
The semantic index is stored locally (or shared securely for teams) for instant querying
Context available
Agent, Tab, and search all draw from the index to provide accurate, codebase-aware results
Project opened
Cursor detects the project and begins indexing files using the custom embedding model
Embeddings generated
Each file is converted into semantic vectors that capture meaning, structure, and relationships
Index stored
The semantic index is stored locally (or shared securely for teams) for instant querying
Context available
Agent, Tab, and search all draw from the index to provide accurate, codebase-aware results