Reference brings local semantic search to AI agents
Reference is a privacy-first local semantic search engine designed specifically to provide AI coding agents with accurate, cited code context without sending data to the cloud. Powered by tree-sitter for code-aware chunking and featuring a live index that updates on file save, Reference embeds a Model Context Protocol (MCP) server offering `/search`, `/explain`, `/find_similar`, and `/check_doc_drift` tools. This allows AI assistants such as Claude Code to locate exact function definitions and code references instantly, eliminating expensive and inefficient grep loops.
Local, agent-oriented semantic search tools like Reference address one of the biggest friction points in AI-assisted development: token burn and context loss from unguided codebase exploration.
- –Tree-sitter chunking preserves structural context far better than standard sliding window text splitters.
- –Zero-cloud architecture ensures intellectual property and sensitive code bases remain strictly local.
- –MCP server integration makes it plug-and-play for modern agentic developer tools.
DISCOVERED
1d ago
2026-08-07
PUBLISHED
1d ago
2026-08-07
RELEVANCE
AUTHOR
Rahul Thennarasu
