Provides AI coding agents with structured Git repository context including project state, code structure, activity, and risk analysis without modifying or uploading code.
Analyzes codebases from local directories, GitHub, and Azure DevOps, providing intelligent context to AI coding assistants through repository structure, critical files, and semantic maps.
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.
Live codebase intelligence for AI agents. Import graph PageRank for file importance, git forensics for co-change coupling and fragile code, convention detection across 16 domains, and blast radius analysis.
Provides structured, token-efficient code context for AI assistants by indexing codebases with AST-level analysis, supporting 17+ languages, enabling semantic search, call-site tracking, and PR attribution.
Deterministic context selection for AI coding agents. Scores and selects the minimal file set for each task, then records
outcomes into a local ledger that compounds into reusable patterns.