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Antigravity 2.0 vs Code Review Graph

Bottom line

Antigravity 2.0 has a free plan plus paid upgrades, while Code Review Graph is free. Code Review Graph is open source and Antigravity 2.0 is not. You can run Code Review Graph on your own machine or server; Antigravity 2.0 is hosted by the vendor.

Which one should you try?

Antigravity 2.0

Freemium

Best for Developers building with AI agents

Visit Antigravity 2.0 See full review

Code Review Graph

Free

Best for Teams using Claude Code, Cursor, or other MCP-compatible AI coding assistants

Visit Code Review Graph See full review

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

Antigravity 2.0

Antigravity 2.0

The vendor describes Project IDX as a browser-based IDE where agents handle multi-step coding tasks end-to-end: writing code, executing it, observing what breaks in a live preview, and self-correcting before handing back control. Multi-model support means you are not locked to a single provider when one model handles your stack better than another. The free tier exists but carries usage caps that surface quickly on longer agentic runs — teams hitting those caps mid-task face a hard stop, not a graceful queue. Browser-based architecture removes local setup friction but also removes offline access and the deep editor customization that engineers who have spent years tuning their environment tend to miss.

Code Review Graph

Code Review Graph

The tool builds a dependency graph of your codebase locally, then exposes that graph through MCP so Claude Code, Cursor, or any compatible assistant can ask targeted questions: which files are affected by this change, what is the impact radius, which communities cluster around this module. For large monorepos, this is the difference between a useful review context and a truncated one. The analysis runs entirely on your machine — no source code leaves the environment. The gap shows up when you need deep semantic understanding beyond structural imports; graph topology tells you what calls what, not whether the logic is correct.

AttributeAntigravity 2.0Code Review Graph
PricingFreemiumFree
Price$0-$200/month—
Pricing checkedJun 11, 2026Not checked yet
Free trialNot statedNot stated
Open sourceNoYes
Has APIYesYes
Self-hosted optionNoYes
PlatformsmacOS, Windows, Linux, Web-basedLinux, macOS, Windows (Python 3.10+)
Released2025-112023
Pros
  • Self-verifying execution loop — the agent runs code, observes live browser output, and revises without waiting for you to relay what broke, which means you stop being the error-relay between your AI tool and your test environment.
  • Multi-model support in a single environment, so switching the underlying model when one handles your framework better is a configuration change rather than a tool migration.
  • Browser-based access with no local setup, which means onboarding a new developer or spinning up a fresh environment takes minutes rather than an afternoon of dependency resolution.
  • Multi-agent task splitting lets separate agents handle discrete parts of a complex task in parallel, cutting the wall-clock time on multi-step workflows that a single-agent loop would process serially.
  • API access means the agentic core can be called from external pipelines, so teams integrating AI into CI or build systems are not forced to use only the browser interface.
  • Reads only changed files and their structural dependencies rather than entire repositories, so your AI assistant's context window goes toward relevant code instead of noise from unrelated modules.
  • Impact radius scoring on change analysis, so reviewers see which downstream files carry the highest risk before opening a single one — rather than manually tracing imports across a large graph.
  • Fully local execution with no cloud dependency, so source code never leaves the environment — a hard requirement for teams under data residency or confidentiality constraints.
  • MIT-licensed with no paid tier and pip installation, so there is no procurement gate, no usage cap, and no feature that unlocks only when you upgrade.
  • Unified graph model across multiple languages, so a polyglot monorepo gets consistent structural queries without separate tooling per language stack.
Cons
  • Free tier usage caps terminate agentic runs mid-task when a multi-step job exceeds the allotment — there is no graceful queue, the session stops, and teams restart manually or upgrade to a paid tier before they have fully evaluated whether the tool fits.
  • No self-hosted option and no offline access: teams with data residency requirements, air-gapped environments, or security policies restricting cloud-only tooling cannot use this at all, and those teams move to locally-deployable alternatives rather than filing exception requests.
  • Browser-based execution means editor customization stops at what Google exposes in the interface — developers who depend on a specific plugin, language server configuration, or terminal workflow find the ceiling fast, and the path forward is maintaining a second local environment for the tasks IDX cannot handle.
  • Complex conditional branching across more than a few agents strains the multi-agent coordination layer; community reports describe tasks with deep dependency chains producing inconsistent results, and teams handling those workflows add manual checkpoints that undercut the automation they bought the tool to achieve.
  • The graph captures import and call structure, not runtime behavior or semantic intent — questions like 'does this change break business logic in the billing module' return no useful answer, and teams with that requirement add a dedicated semantic search tool, maintaining two systems in parallel.
  • MCP is the only consumption interface; development environments without MCP support get nothing from this tool. Teams using IDE plugins or assistants that do not expose MCP cannot integrate it without building a custom bridge.
  • Community detection and architecture overview queries return structural clusters, which require a developer to interpret the output against domain knowledge — for teams onboarding to an unfamiliar codebase, the graph answers 'what talks to what' but not 'why.' Teams that need the 'why' typically switch to tools that ingest documentation and comments alongside the dependency graph.

Made up your mind?

Antigravity 2.0

Freemium

Best for Developers building with AI agents

Visit Antigravity 2.0 See full review

Code Review Graph

Free

Best for Teams using Claude Code, Cursor, or other MCP-compatible AI coding assistants

Visit Code Review Graph See full review

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Specs come from each tool's own site and docs (how we test). AIDiveForge is editorially independent.

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