code-context-engine vs Graft
code-context-engine: Code Context Engine (CCE) indexes your codebase using tree-sitter parsing and vector embeddings, allowing AI coding agents to search for relevant code instead of re-reading entire files. It saves up to 94% input tokens, works across multiple editors (Claude Code, VS Code, Cursor, Gemini CLI, Codex CLI), and runs entirely locally for privacy. With built-in compression, graph expansion, and cross-session memory, CCE reduces costs and speeds up responses.; Graft: Graft is an open-source context layer designed to accelerate and optimize coding agents like Claude Code, Cursor, and Gemini by providing deep contextual understanding of large codebases. It builds a human-readable code graph and linked markdown nodes, enabling agents to operate faster, cheaper, and with higher correctness by avoiding repeated code exploration.
TL;DR
Reduce Claude Code costs by cutting input tokens
- You want to generate a readable, interconnected Markdown knowledge graph of your repository so coding agents (Claude Code, Cursor) can grep and explore without expensive re-indexing.
- You want to reduce context token waste by giving agents precise map-like documentation of modules and call paths.
- You need an enterprise graph database with semantic vector embeddings and Cypher queries; code-graph-rag with Neo4j fits that scale.
- You only have a small, single-file script or a trivial repository.
Side-by-Side Comparison
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