Local-first codebase context engine that parses code into a ranked dependency graph and serves it to AI tools via MCP for deep structural understanding.
A local-first codebase intelligence layer for AI coding agents, providing a persistent, queryable model of a repository via an MCP server and CLI to enable structure queries instead of reading many files.
Local-first code intelligence MCP server that enables coding agents to search code, inspect structure, read exact ranges, and explore Git history with explicit token budgets.
Provides a local-first code indexing and search engine for coding agents via MCP, enabling precise codebase queries, symbol lookup, and freshness-aware retrieval.
Local repository intelligence MCP server that builds a reusable graph of code structure for AI coding agents, providing 34 network-free tools for understanding, searching, and analyzing repositories without data leaving the machine.
A local code-intelligence engine for AI agents that indexes repositories into a PostgreSQL-backed code graph and serves structured, token-budgeted context over MCP and HTTP, enabling targeted queries on symbols, dependencies, contracts, and impact analysis.