Contextful

This is an alpha-stage context engine that indexes your codebase once and returns ranked, cited evidence packs instead of making agents repeatedly read dozens of files. It exposes seven MCP tools, anchored by context_pack(query, budget, scope), which replaces scattered grep and file read calls with a single token-budgeted response. You also get search_code forlex/BM25 search, trace_path for graph traversal across symbols and modules, impact_analysis for reverse dependencies, and write_lesson for storing evidence-backed memory that persists across sessions. Uses SQLite with FTS5 for local-only indexing. Set it up with npx @inferensys/contextful init, then run it as an MCP server. Reach for this when context window bloat and redundant file reads are slowing down your agent workflows.