Antigravity — Repo Q&A Engine + Optional MCP

Main

• Run ag-refresh first: it builds the knowledge base so later Q&A is grounded in module docs rather than random file picks.

• Use ag-ask as your default onboarding interface: ask architecture questions and require file-path evidence in answers.

• Keep .antigravity/ under version control when useful so context stays consistent across IDEs and teammates.

• Enable MCP only when you need tool-style integration; the CLI workflow already works across hosts per README.

README (excerpt)

Antigravity — Workspace Template for Claude Code, Codex CLI & Cursor

Multi-agent knowledge engine + optional MCP server that turns any repo into a queryable AI assistant. Works with Claude Code, Codex CLI, Cursor, Windsurf, and Gemini CLI.

ag-refresh builds a knowledge base. ag-ask answers questions. Any LLM, any IDE.

Language: English | 中文 | Español

Why Antigravity?

An AI Agent's capability ceiling = the quality of context it can read.

Source-backed notes

• README documents the core commands ag-refresh and ag-ask, and shows manual install via pip install git+...#subdirectory=cli/engine.
• README claims a head-to-head eval on 36 questions and includes quantitative results and dates (see README section headings).
• Repo is MIT licensed and supports multiple hosts (Claude Code, Codex, Cursor) per README badges/table.

FAQ

• Do I need MCP enabled?: No—README shows CLI-only flows; MCP is optional when you want tool integration.
• What are the core commands?: ag-refresh builds/refreshes knowledge; ag-ask answers questions over the current workspace (README).
• How long does a first setup take?: Expect ~15–35 minutes depending on model/provider setup and repo size; tune timeouts in .env.