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Rank #4 of 6 in AI Code Review

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Greptile

YC W24

Tabnam, Inc. (dba Greptile) · commercial

greptile.com ↗Try it →
PA Score27/100AGENT-READY39/100BUILT-IN AI31/100API9/100
MCP✓CLI✓API~
npm 10.3k/wk
ArenasAI Code Review#4/6

Access

Open app ↗API docs ↗CLI docs ↗MCP docs ↗

Install

npmnpm install -g greptile@latest

Compare head-to-head

CodeRabbit logovs CodeRabbitGraphite logovs GraphiteQodo logovs QodoCursor Bugbot logovs Cursor Bugbotcubic logovs cubic

Alternatives to Greptile →

Showcase

Greptile homepage screenshot
homepage · captured Sep 2026 · view live ↗
Greptile docs screenshot
docs · captured Sep 2026 · view live ↗

Try itExperimental

See what an agent can do with Greptile before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; commands tagged live-capable can re-run against the real endpoint from our edge, right now (▶ run live — the exact same request, live and recorded lines always labeled); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).

$curl -s -X POST https://api.greptile.com/v2/repositories -H 'Content-Type: application/json' -d '{}'recorded session — replayed, not live
recorded 2026-09-10 · exit 0 · captured verbatim by our probe harness, secrets redacted · pure-HTTP probe — ▶ run live re-runs it from our edge

Verified integrations

No integration evidence found in our corpus for this product yet — that means none was found, never that it doesn’t integrate.

By theme — the product's score on each story themeBy theme

Agenticness — how well agents can access and operate the productAgenticnessevidence →

How well agents can access and operate the product

31.6/100

Autofix agents — stories about autofix agents in this arenaAutofix agentsevidence →

Stories about autofix agents in this arena

72.4/100

Automation depth — how much of the product can run unattendedAutomation depthevidence →

How much of the product can run unattended

23.3/100

Codebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understandingevidence →

How deeply the tool maps your repo — cross-file context, architecture awareness, history

35.4/100

Interaction — how you steer it — commands, replies, review conversations, configurability in the loopInteractionevidence →

How you steer it — commands, replies, review conversations, configurability in the loop

30.0/100

Openness — open source, data portability, and self-hosting storiesOpennessevidence →

Open source, data portability, and self-hosting stories

27.0/100

Pr integration — stories about pr integration in this arenaPr integrationevidence →

Stories about pr integration in this arena

44.0/100

Privacy posture — data-handling and privacy storiesPrivacy postureevidence →

Data-handling and privacy stories

28.0/100

Quality gates — stories about quality gates in this arenaQuality gatesevidence →

Stories about quality gates in this arena

0.0/100

Review accuracy — stories about review accuracy in this arenaReview accuracyevidence →

Stories about review accuracy in this arena

42.0/100

Surfaces — where it meets your workflow — IDE, CLI, web, PR comments, CI checksSurfacesevidence →

Where it meets your workflow — IDE, CLI, web, PR comments, CI checks

33.0/100

Workflow config — stories about workflow config in this arenaWorkflow configevidence →

Stories about workflow config in this arena

51.7/100

Story verdicts — every judged story with its evidenceStory verdicts

?

Sorted by importance (agentic first) (high → low) · 53/53 stories · click a row’s chevron for the rationale and evidence

Connect an agent via an official MCP server G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full8/10T

Drive the product through a documented public API G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3partial6/10T

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness3disputed5/10D

Plug MCP servers into this product so it can use their tools G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3none0/10

Point an agent at llms.txt or agent-oriented docs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Run the product headlessly / in CI for automation G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Use an official CLI G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Set up automations that run autonomously in the background G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full7/10C

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2disputed6/10D

Operate the product with natural-language commands G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial5/10X

Build against official SDKs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Explore an interactive API reference with runnable examples G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Rely on versioned APIs with a documented deprecation policy G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Issue scoped/least-privilege API credentials for an agent G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2noneuntestednone yet

Subscribe to events via webhooks G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2noneuntestednone yet

Test against a sandbox environment without touching production data G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness1full6/10C

I turn a review finding into an applied fix — a committed patch or an agent-generated follow-up — without leaving the PR C

Fixes

developerAutofix agents — stories about autofix agents in this arenaAutofix agents3full8/10C

Self-host the core product G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3full7/10C

The reviewer installs as a GitHub/GitLab app and posts reviews as native inline comments on my pull requests within minutes C

Platforms

developerPr integration — stories about pr integration in this arenaPr integration3partial7/10X

I configure the reviewer with a versioned config file in my repo — path filters, per-path instructions, review profiles C

Config

engineering leadWorkflow config — stories about workflow config in this arenaWorkflow config3partial6/10C

Review comments reflect the whole repository — call sites, related modules, existing conventions — not just the changed hunks C

Context

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding3partial6/10X

The reviewer catches real bugs in my PR — logic errors, race conditions, broken edge cases — not just style nits C

Detection

developerReview accuracy — stories about review accuracy in this arenaReview accuracy3partial6/10X

The reviewer keeps noise low — few false positives, deduplicated comments, severity labels — so my team doesn't tune it out C

Noise

engineering leadReview accuracy — stories about review accuracy in this arenaReview accuracy3partial6/10X

Define rules that trigger actions automatically on events G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth3partial5/10C

Review comments include committable suggested diffs I can apply with one click C

Suggestions

developerPr integration — stories about pr integration in this arenaPr integration3partial5/10C

Prevent my data from being used to train AI models G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture3partial4/10C

Export all of my data in open formats and leave G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3none0/10

Review findings hand off cleanly to my coding agent — copyable fix prompts or direct integration with Claude Code, Cursor, or Codex C

Handoff

ai-native userAutofix agents — stories about autofix agents in this arenaAutofix agents2full9/10C

I encode my team's own review guidelines — natural-language rules, AST patterns, or linked style guides — and the reviewer enforces them C

Rules

engineering leadWorkflow config — stories about workflow config in this arenaWorkflow config2full8/10C

The reviewer holds the line on AI-generated PRs — it verifies agent-authored code at a volume no human team could review C

Ai authored

ai-native userAutofix agents — stories about autofix agents in this arenaAutofix agents2full8/10X

Every PR gets an auto-generated summary and change walkthrough so human reviewers orient fast C

Summaries

developerPr integration — stories about pr integration in this arenaPr integration2full7/10X

Push back on a bad review comment and the reviewer learns — it stops repeating the same rejected feedback C

Learning

developerReview accuracy — stories about review accuracy in this arenaReview accuracy2partial7/10C

Pushing new commits triggers an incremental re-review that tracks what was fixed instead of repeating old comments C

Updates

developerPr integration — stories about pr integration in this arenaPr integration2partial7/10C

The reviewer builds a persistent memory of my team's conventions and past review decisions and applies it to future PRs C

Memory

ai-native userCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding2full7/10C

Choose where my data is stored (region/residency) G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partial6/10C

I define custom agentic pre-merge checks in plain language — 'docs updated', 'tests cover new paths' — that run on every PR C

Checks

ai-native userAutofix agents — stories about autofix agents in this arenaAutofix agents2partial6/10C

I get the same review inside my IDE before I push, catching issues while the code is still in my editor C

Ide

developerSurfaces — where it meets your workflow — IDE, CLI, web, PR comments, CI checksSurfaces2partial6/10T

Perform bulk operations across many items at once G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2partial6/10C

Reviews flag security problems in the diff — injection risks, leaked secrets, insecure patterns — alongside functional bugs C

Security

security engineerReview accuracy — stories about review accuracy in this arenaReview accuracy2full6/10X

Control data retention and deletion G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partial5/10C

Do everything through the API that I can do in the UI G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partial5/10T

I reply to the reviewer in the PR thread to ask questions, get explanations, or issue commands — and it answers in context C

Chat

developerInteraction — how you steer it — commands, replies, review conversations, configurability in the loopInteraction2partial5/10X

I run reviews from a CLI against local diffs or in CI scripts, with machine-readable output my tooling can consume C

Cli

developerSurfaces — where it meets your workflow — IDE, CLI, web, PR comments, CI checksSurfaces2partial5/10T

Opt out of telemetry and usage tracking G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partial4/10C

Read the product's source under an open license G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2none0/10

The reviewer understands changes that span multiple repositories or a large monorepo and reviews them coherently C

Context

engineering leadCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding2none0/10

Schedule recurring jobs or workflows G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2noneuntestednone yet

The reviewer can gate merges — a required status check or blocking review that enforces resolution of critical findings C

Gates

engineering leadQuality gates — stories about quality gates in this arenaQuality gates2noneuntestednone yet

I roll out org-level review defaults across hundreds of repos and manage exceptions centrally C

Governance

engineering leadWorkflow config — stories about workflow config in this arenaWorkflow config1partial7/10C

I control when reviews run — skip drafts, trigger on demand, filter by branch or label — so the bot shows up only when wanted C

Control

developerInteraction — how you steer it — commands, replies, review conversations, configurability in the loopInteraction1partial5/10C

Version, review, and roll back my automations G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth1partial4/10C

I see dashboards of findings, acceptance rates, and review coverage across my org C

Analytics

engineering leadQuality gates — stories about quality gates in this arenaQuality gates1noneuntestednone yet

Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 37 stories with headroom

What would move Greptile’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.

  1. Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools

    nonemoves agent-readyimpact 45

    All MCP-related evidence describes Greptile exposing its own MCP server so other tools (Cursor, Claude Code, VS Code, Codex) can pull Greptile's review data and fixes (docs-23, docs-24, probe-4) — this is Greptile acting as the MCP server, not as a client that consumes external MCP servers' tools.

  2. Openness — open source, data portability, and self-hosting storiesExport all of my data in open formats and leave

    nonemoves PA Scoreimpact 30

    No evidence of any data export feature or open-format data portability for user data (reviews, patterns, learned rules, etc.); self-hosting only affects where data lives, not exportability.

  3. Agenticness — how well agents can access and operate the productIssue scoped/least-privilege API credentials for an agent

    nonemoves agent-readyimpact 30

    Missing: any documentation of API key scopes, permission levels, or least-privilege token issuance for agent access.

  4. Agenticness — how well agents can access and operate the productBuild against official SDKs

    nonemoves agent-readyimpact 30

    Evidence shows Greptile offers a CLI and an MCP server for agent integration, but no official SDKs (client libraries) are documented anywhere, and the openapi probe returned 404 for all candidate API-spec paths, indicating no public API/SDK surface to build against.

  5. Agenticness — how well agents can access and operate the productSubscribe to events via webhooks

    nonemoves agent-readyimpact 30

    No evidence of any webhook subscription mechanism for events; Greptile's integrations documented are MCP, CLI, and agent 'Fix with your Agent' flows, but no docs mention webhooks for subscribing to review or event notifications.

  6. Agenticness — how well agents can access and operate the productExplore an interactive API reference with runnable examples

    nonemoves API qualityimpact 30

    No evidence of an interactive API reference or runnable examples; the openapi.json/swagger.json probe explicitly returned 404s across all candidate paths, and docs only describe CLI/MCP/dashboard workflows, not an API explorer.

  7. Agenticness — how well agents can access and operate the productDownload a machine-readable API spec (OpenAPI or equivalent)

    nonemoves API qualityimpact 30

    A direct probe found no OpenAPI/Swagger spec at any standard location (all 404s), and no other evidence mentions a machine-readable API spec being available for download.

  8. Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy

    nonemoves API qualityimpact 30

    Missing: versioned API docs, explicit deprecation policy, changelog entries about API version sunsetting.

Showing the top 8 of 37 — every none/partial verdict in the story verdicts table is headroom.

Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.

Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map11 surfaces · 40 covered stories

Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.

docs34 stories

Hacker News11 stories

CLI docs11 stories

Independence docs8 stories

Changelog docs5 stories

Security check docs5 stories

Security docs5 stories

Trex docs5 stories

OpenAPI spec3 stories

Learning docs3 stories

llms.txt1 story

Probe proofs — replayable recordings from the probe harnessProbe proofs

Replayable recordings from our probe harness — see the Prove-It protocol to submit one.

$curl -s -X POST https://api.greptile.com/v2/repositories -H 'Content-Type: application/json' -d '{}'reproduced
$ curl -s -X POST https://api.greptile.com/v2/repositories -H 'Content-Type: application/json' -d '{}'
{"error":"No API [redacted] provided"}
proves: Drive the product through a documented public APIrecorded 2026-09-10
$npx -y greptile --versionreproduced
$ npx -y greptile --version
3.5.2
proves: Use an official CLIproves: I run reviews from a CLI against local diffs or in CI scripts, with machine-readable output my tooling can consumerecorded 2026-09-10
$curl -s -X POST https://api.greptile.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # FULL keyless handshakereproduced
$ curl -s -X POST https://api.greptile.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'  # FULL [redacted]less handshake
{"jsonrpc":"2.0","id":1,"result":{"protocolVersion":"2025-03-26","capabilities":{"tools":{}},"serverInfo":{"name":"Greptile MCP Server","version":"1.0.0"},"instructions":"Successful tool results are JSON objects encoded in the text field of the first MCP content block: parse content[0].text before reading fields. Tool errors set isError: true and return a plain-text explanation instead. List tools use either page or offset as documented; a field named total is not necessarily an organization-wide count, so follow each tool's result guidance.\n\nAccount: get_me returns the caller and every orga
proves: Connect an agent via an official MCP serverrecorded 2026-09-10
$curl -s https://www.greptile.com/docs/llms.txt | head -6reproduced
$ curl -s https://www.greptile.com/docs/llms.txt | head -6
# Greptile

- [Overview - What is Greptile?](https://www.greptile.com/docs/introduction.md)
- [5-Minute Quickstart](https://www.greptile.com/docs/quickstart.md): Set up Greptile AI code reviews in 5 minutes. Connect GitHub or GitLab, configure review triggers, and get automated feedback on your first pull request.
- [CLI Onboarding](https://www.greptile.com/docs/code-review/cli-onboarding.md): Set up Greptile from your terminal with greptile onboard — or hand this page to your coding agent and have it run the setup for you.
- [[redacted] Features](https://www.greptile.com/docs/code-review/[redacted]-features.md): Discover Greptile's [redacted] features: full codebase context, high-signal reviews, team learning, IDE integration via MCP, and enterprise-grade deployment options.
proves: Point an agent at llms.txt or agent-oriented docsrecorded 2026-09-10
$curl -sL https://www.greptile.com/docs/quickstart.md | head -12reproduced
$ curl -sL https://www.greptile.com/docs/quickstart.md | head -12
> ## Documentation Index
> Fetch the complete documentation index at: https://www.greptile.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# 5-Minute Quickstart

> Set up Greptile AI code reviews in 5 minutes. Connect GitHub or GitLab, configure review triggers, and get automated feedback on your first pull request.

This guide covers GitHub/GitLab setup, repository configuration, and your first automated code review.

## Installation & Setup
proves: Point an agent at llms.txt or agent-oriented docsrecorded 2026-09-10

Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence

10 of 20 testable claims verified · 1 contradicted → integrity 40/100

30 distinct capability claims found in Greptile’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.

10

Verified

9

Unverified

1

Contradicted

19

Undersold

Verified (16)
Unverified (15)
Contradicted (1)
Undersold (19)
Claims outside our story set (3)

Real capability claims found in Greptile’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.

  • “Requires allowlisting Greptile's IP range if GitHub/GitLab restricts inbound traffic”

    source ↗

  • “Automatically generates unit tests for new or changed code in a PR”

    source ↗

  • “Vendor states it may aggregate and anonymize customer data to train and improve its AI models”

    source ↗
Suggest a story for these →

Business model

free-tiersubscription-per-seatusage-basedenterprise-custom

Starter free for 1 active developer; Pro $30/seat/mo with 50 review credits per seat ($1 per extra credit; a TREX sandbox review is 3 credits); self-hostable Enterprise is custom; free for qualified MIT/Apache OSS.

pricing ↗

Score trend

How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.

PA Score28 (Sep 10 '26)27 (Sep 16 '26)
Agent-ready40 (Sep 10 '26)39 (Sep 16 '26)

Try Experimental

Run it in the microterminal →

Recorded agent sessions — and a live MCP handshake where the vendor ships one.

Flag

⚑ Flag a verdict

Think a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.

Badge

Embed this product's score badge →

Hotlinked SVG — always shows the live current score.

For agents

This page as markdown/llms.txt

Data

Evidence (JSON)Verdicts (JSON)

Agent surface uptime MCP up · llms.txt up (tracking since Sep 11 '26)