A semantic code retrieval engine for AI agents that enables hybrid search, graph expansion, and token-aware context packing, integrating with MCP to provide precise code context to LLMs.
Token-optimized semantic code search with automatic context expansion for AI coding assistants, enabling efficient discovery of code relationships and reducing token usage.
Adds semantic code search to AI coding agents, enabling natural language queries across entire codebases to retrieve relevant code chunks, saving tokens and providing deep context.
Persistent, cross-tool memory for AI coding assistants, enabling context retention across sessions, tools, and devices with a three-tier memory model and hybrid search.
A memory system for AI coding tools that stores and retrieves codebase context with project isolation. Enables coding assistants to maintain searchable memory of code snippets, comments, and runtime traces with full source traceability.
Provides semantic code search and retrieval capabilities for AI agents, enabling them to query codebases using natural language with automatic learning, hybrid search, and intelligent chunking of functions and classes.