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Bloom vs Code Review Graph

Bottom line

Bloom has a free plan plus paid upgrades, while Code Review Graph is free.

Which one should you try?

Bloom

Freemium

Best for Regression testing, release gating, and tracking mitigations over time

Visit Bloom 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.

Bloom

Bloom

Bloom generates targeted evaluation suites for arbitrary behavioral traits.

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.

AttributeBloomCode Review Graph
PricingFreemiumFree
Price$17-$100+/mo—
Pricing checkedOct 19, 2026Not checked yet
Free trialNot statedNot stated
Open sourceYesYes
Has APIYesYes
Self-hosted optionYesYes
PlatformsPython; integrates with Anthropic and OpenAI models via LiteLLM; supports Weights & BiasesLinux, macOS, Windows (Python 3.10+)
LanguagesPython—
Released2025-12-202023
Pros
  • Reproducible and targeted evaluations that quantify frequency and severity across automatically generated scenarios
  • Evaluations correlate strongly with hand-labelled judgments and reliably separate baseline models from intentionally misaligned ones
  • Researchers can extensively configure Bloom's behavior, through choosing models for each stage, adjusting interactions' length and modality
  • Using Bloom evaluations took only a few days to conceptualize, refine and generate
  • Integrates with Weights & Biases for experiments at scale and exports Inspect-compatible transcripts
  • 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
  • Bloom is only as robust as the seeds and judging logic that power it; teams should treat seeds as living governance artifacts, and for ambiguous or highly contextual behaviors, periodic manual review is still necessary
  • Bloom's evaluation suite is unlikely to match the precise distribution of scenarios found in existing benchmarks, and since model behavior can be sensitive to context and prompt variations, direct comparisons are unreliable
  • 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?

Bloom

Freemium

Best for Regression testing, release gating, and tracking mitigations over time

Visit Bloom 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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