Graft

Graft is an open-source CLI tool built by Nanonets that creates a persistent context graph for large codebases, enabling AI coding agents like Claude Code, Cursor, Codex, and Gemini to work faster and more accurately without re-exploring the repo from scratch on every task. It is licensed under MIT, runs 100% locally with no telemetry, and requires no vector embeddings or external database. The project is published on npm as @nanonets/graft and the source lives at github.com/NanoNets/context-graph-engine.

What It Is

Graft solves a specific problem: every time an AI coding agent starts a task, it re-explores the codebase from zero — grepping files, following imports, and rebuilding a mental map it already built an hour ago. Graft builds that understanding once and writes it into the repo as a folder of linked markdown files (graft/), one node per system, API, or concept. The graph is just files your agent reads, not a running server or warm index. Because it lives in git, every teammate and their agent inherits it automatically.

How the Graph Gets Built

Graft uses two passes to construct its context layer:

• Structural pass (free, no model): Tree-sitter parses 20+ languages deterministically, extracting functions, classes, call edges, and imports into graft/.graph/wiring.json. This never calls an LLM and needs no API key.
• LLM enrichment pass (--deep): A second pass summarizes each file and groups them into plain-English concept nodes with typed links (uses, produces, validates, configures, extends). Any provider works — OpenAI, Anthropic, OpenRouter, Fireworks, Groq, LiteLLM, or a local model — under your own key.

Every pass is cached by content hash, so rebuilds only touch changed files. On the Graft repo itself (124 files), a cold build takes 0.74s; a rebuild after one edit takes 0.18s.

Benchmark Results

The Graft README reports a 162-run controlled benchmark comparing cold Claude Code against Claude Code with Graft, using the same agent and file tools with only the context differing:

• 46% fewer tool calls per task
• 42% fewer tokens consumed
• 60% less latency per task
• +12 correctness points on SWE-bench Verified (66% vs 54% on 50 instances)

On popular open-source repos like PocketBase, the README claims Graft runs "up to 4× cheaper and 3× faster" while reproducing all five tested merged PRs by touching the same files the maintainers did.

Agent Integration and MCP Server

graft init wires Graft into whichever coding agents you use. Supported agents include Claude Code, Cursor, Codex, Gemini, Kiro, Windsurf, GitHub Copilot, and AdaL. Claude Code gets the deepest integration: a live statusline showing graph size and staleness, auto-sync after every edit, and context injection at each prompt.

Graft also ships an MCP server with six tools available to any MCP-compatible agent:

• graft_find_code — ranked nodes with file:line for a natural-language question
• graft_file_api — every signature in a file without bodies
• graft_trace_calls — blast radius for any symbol
• graft_find_all — exhaustive regex search grouped by enclosing symbol
• graft_repo_map — directory clusters, hubs, and hotspots
• graft_check_freshness — drift detection between graph and working tree

Architecture and Deployment Model

Graft is entirely local. The graph is a folder of markdown files committed alongside your code — no daemon, no database, no embeddings server to keep warm. The structural graph (graft build) is deterministic and costs nothing to run. The LLM-enriched layer (graft build --deep) calls your chosen provider under your own key; Graft itself never sees your API key or code. There is no telemetry. The graft viz command serves an interactive local graph viewer (prebuilt, no dev server needed) showing both the architecture graph and the per-symbol code graph with directional edge highlighting.

Update: Active Development as of Mid-2026

The GitHub repository (NanoNets/Graft, also mirrored as context-graph-engine) was created in July 2026 and last pushed in August 2026, with 2,844 stars and 248 forks at time of indexing. The npm package is @nanonets/graft. The project is under active development; the README notes that inlining crux excerpts into markdown nodes is a planned next step, and the SWE-bench Verified results are described as provisional.