
Reference
Local semantic search for AI agents
About Reference
Reference is a powerful local semantic search tool designed specifically for AI agents and developers working with code and files. Unlike cloud-based solutions, it runs entirely on your machine, ensuring data privacy and security. Its core feature set includes a live, continuously updating index that intelligently chunks code using tree-sitter, enabling precise and context-aware searches. Users can ask complex questions like 'how did I implement rate limiting here?' and receive exact code snippets cited down to the specific function, significantly improving debugging and code comprehension. The built-in MCP server offers endpoints such as /search, /explain, /find_similar, and /check_doc_drift, allowing AI models like Claude Code to generate accurate, citation-based results without wasting tokens on inefficient grep loops. Suitable for developers, AI engineers, and teams prioritizing privacy and precision, Reference elevates code search from simple keyword matching to an intelligent, code-aware experience.
Screenshots




Pros
- ✓Local, privacy-focused search avoiding data leaks
- ✓Code-aware chunking with tree-sitter for precise results
- ✓Live index updates as files are saved for real-time accuracy
- ✓Built-in MCP server with multiple endpoints for AI integration
- ✓Highly specific code citations improve debugging and learning
Cons
- ✗Potential learning curve for users unfamiliar with advanced search features
- ✗Limited information on pricing and potential resource requirements
- ✗No mention of a free tier or open-source options
Use Cases
Pricing
Likely follows a freemium model with a free tier for basic usage and paid plans offering advanced features or enterprise integrations, but specific details are not publicly available.
Quick Info
Topics
Makers
Rahul Thennarasu
Alternatives
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