Semantic Vision

Interactive call graph, impact analysis, and AI-generated docs for your codebase, right inside the editor — the same engine as the Semantic Vision web app, as a panel next to your code instead of a separate browser tab.

What it does

• Open Graph (semanticVision.openGraph) — opens the full call graph in a panel, centered on whichever file is active in the editor. Click any node to jump straight to that function or class in your code.
• Impact Analysis at Cursor (semanticVision.impactAnalysisAtCursor, also on the editor right-click menu) — resolves your cursor position to a graph node and highlights every direct and transitive caller, so you can see a change's real blast radius without leaving your place in the file.

Everything else the graph supports — execution flowcharts, the complexity report, AI-generated documentation, code-to-data lineage — is available from the same panel once it's open, unchanged from the web app.

Requirements

This extension is a thin client: it renders the same frontend as the web app, backed by a local FastAPI server that does the actual parsing.

• semanticVision.backendUrl (default http://localhost:8000) — where that server is expected to answer. If something is already running there (e.g. via docker compose up, see the main project's README), the extension uses it as-is.
• semanticVision.backendPath — optionally, an absolute path to a local Semantic Vision checkout (the directory containing pyproject.toml). When set, the extension starts the backend for you with uv run uvicorn semantic_vision.api.app:app, the same command the project documents for local development. This requires uv on PATH and a prior uv sync in that checkout.

Nothing about your code is ever executed or sent anywhere — parsing is static, and the backend runs entirely on your own machine.

Getting started

1. Install this extension.
2. Either start the backend yourself (uv run uvicorn semantic_vision.api.app:app from a Semantic Vision checkout, or docker compose up), or set semanticVision.backendPath to have the extension start it automatically.
3. Open a file in a supported repository (Python, or JavaScript/TypeScript) and run Semantic Vision: Open Graph from the Command Palette.

Learn more

Full documentation, screenshots, and setup guides (AI provider setup, code-to-data lineage, multi-language support) live in the main project's README and guides/ directory.