Mira
Mira is a self-hosted, open-source AI code reviewer that indexes your whole repo and reviews pull requests with the LLM of your choice.
If your security posture forbids shipping source to a hosted reviewer, Mira is the rare open-source option that actually covers the full surface — indexing, security scanning, custom rules, a learning loop — with no license cost. The catch is that you own deployment, upgrades, and the LLM bill, and Bitbucket isn't supported yet. Pick it when data control outranks convenience; skip it if nobody wants to run a container and register a GitHub App.
Verified 4d ago · liveness 74/100 · cite: rightaichoice.com/tools/mira
- Engineering teams whose security policy forbids sending source code to a hosted reviewer
- Regulated or privacy-conscious orgs that want self-hosted pull request review with no telemetry and no per-seat fee
- GitHub, GitLab, and Forgejo/Codeberg teams trying to cut manual load on a busy PR queue
- Platform teams comfortable with Docker, webhooks, environment variables, and owning upgrades
- Teams that want a fully managed, zero-deployment reviewer and will trade data control for that convenience
- Bitbucket users — the adapter is still listed as coming soon, so it's unsupported today
- Startups with nobody available to run a container, register a GitHub App, and apply upgrades
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Skip Mira if you want a managed reviewer you never have to deploy or upgrade, or if you are on Bitbucket, since that adapter is still listed as coming soon.
You pay your LLM provider directly for every review, so a busy PR queue with a premium model can cost more per month than a per-seat hosted plan looks like on paper.
Mira is free under Apache 2.0 — no license key, no seat pricing, no paid tier. Your only recurring cost is the LLM provider bill. Against hosted reviewers like CodeRabbit that charge per seat per month, Mira scales down to zero software cost for a small team and scales up without a per-head multiplier for a large one. The crossover favors Mira when headcount grows, and favors hosted services when nobody on the team wants to run the container.
In short
Mira — Mira is a self-hosted, open-source AI code reviewer that indexes your whole repo and reviews pull requests with the LLM of your choice. Best for Engineering teams whose security policy forbids sending source code to a hosted reviewer, Regulated or privacy-conscious orgs that want self-hosted pull request review with no telemetry and no per-seat fee, GitHub, GitLab, and Forgejo/Codeberg teams trying to cut manual load on a busy PR queue. Free to use.
What's new in Mira
Checked 4 days agoAcross the latest 4 updates: 4 feature updates.
0.9.1 — Codex CLI provider, PR-description summaries, xhigh review reasoning
Adds a Codex CLI provider so deployments with an OpenAI Codex login can run reviews without an HTTP API key, optional AI-generated PR-description summaries, and xhigh reasoning effort alongside off/low/medium/high/max.
0.9.0 — Layered security review and OpenAI Responses API support
Adds a dedicated security-model tier with optional agentic read_file/grep_repo verification, a deterministic secrets scan, review-time OSV dependency checks, and OpenAI Responses API support via llm.api_style: responses. Lua joins the indexed languages.
0.8.1 — Agentic tools on indexed repositories
The main reviewer can call read_file and grep_repo even when an index already exists, so it can verify callers and dispatch paths beyond pre-fetched context. Walkthrough parsing also tolerates malformed model output.
0.8.0 — Opt out of per-commit reviews
review.review_on_synchronize (default true) controls whether every push to an open PR triggers a review; turn it off and Mira reviews only on open/reopen, saving tokens and cutting noise.
What people actually say about Mira — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
86 mentions across 6 sources (Hacker News, YouTube, Product Hunt, App Store, GitHub, Lemmy) · researched Aug 27, 2026.
Average across the 6 sources that answered — each source counts once, not each post.
- +Full-repo indexing gives project-wide context, not just a diff.
- +Bring-your-own-LLM: pay providers directly, no markup.
- +Fully open-source and self-hosted; complete data control.
- +Severity and confidence scoring helps triage review comments.
- +Deduplication and comment cap reduce noise on large PRs.
- −Setup requires Docker and DevOps knowledge; not turnkey.
- −Documentation is sparse for advanced setups like Postgres.
- −GitHub Actions integration requires manual webhook setup.
- −Learning loop's quarantine can hide valid findings.
- −Community support is thin; sparse on-topic discussions.
- • Infrastructure costs: you must run a server or container (Docker/Postgres) yourself
- • LLM API costs: you pay the model provider directly for every review call
- • Time cost: DevOps setup and maintenance are on you
Viability Score
How well maintained and how widely used is Mira? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Full-repository indexing so every pull request review runs against whole-project context
- Inline PR comments with severity sorting and confidence scoring
- PR walkthroughs with Mermaid sequence diagrams
- Blast-radius reporting with in-repo callers and cross-repo dependents
- Cross-PR overlap detection for merge-conflict risk and duplicate effort
- Deduplication of findings across chunks and files, plus per-PR comment caps
- GitHub suggestion blocks for one-click applied fixes
- Per-repo and global review rules defined in .mira.yaml
- Learning loop that synthesizes rules from rejected comments and quarantines new ones
- Layered security review with a dedicated security-model tier
- Optional agentic read_file and grep_repo verification on indexed repositories
- Deterministic regex-and-entropy secrets scan
- Review-time OSV dependency checks plus OSV scanning tied to the codebase index
- Org-wide package search across repositories
- Optional AI-generated PR-description summaries
About Mira
Mira is an Apache 2.0 AI code reviewer you run yourself. Point it at GitHub, GitLab, or Forgejo (Codeberg included), and it watches your pull and merge requests, then posts inline comments and walkthroughs using whichever model you supply — Anthropic, OpenAI, Google, DeepSeek, or anything reachable through OpenRouter. You bring the key and pay your provider directly; there's no license key and no seat fee. The thing that separates it from diff-only bots is indexing. Mira reads the whole repository, so each finding is judged against your actual codebase rather than the changed lines alone. Blast-radius reports list in-repo callers and cross-repo dependents, and cross-PR overlap detection flags merge-conflict risk and duplicated effort before two reviewers collide. Noise control is where most reviewers get abandoned, and Mira attacks it from several angles: confidence thresholds, deduplication across chunks and files, severity sorting, and per-PR comment caps. Teams encode their conventions in .mira.yaml per repo or globally, and a learning loop synthesizes candidate rules from comments you reject, holding each one in quarantine until it proves out. v0.9.1 (2026-09-22) adds a Codex CLI provider so a deployment with an OpenAI Codex login can review without an HTTP API key, optional AI-written PR descriptions, and an xhigh reasoning setting. Also in the box: a dedicated security-model tier, a deterministic secrets scan, review-time OSV dependency checks, OSV scanning tied to the index, and org-wide package search. One Docker image on SQLite or Postgres, no phone-home, same image on Railway, Fly.io, or Render. Against CodeRabbit or Copilot code review, you trade zero setup for data control.
Behind the Verdict
We'd reach for Mira when the review bot has to live inside our own network. Running a single Docker image against SQLite or Postgres, with no telemetry and no per-seat line item, is a genuinely different proposition from paying per developer for CodeRabbit or folding review into Copilot. The indexing is the reason to care. Diff-only reviewers comment on the lines in front of them; Mira reads the repository, then reports blast radius with in-repo callers and cross-repo dependents. In practice that's the difference between "this looks wrong" and "this breaks three callers in another service." Cross-PR overlap detection is the quiet win — it catches two engineers solving the same problem in parallel before both get merged. Our caveat is the same as ever with self-hosted tools: you are the SRE. Someone has to register the GitHub App, hold the private key, wire webhooks, and apply upgrades. Budget an afternoon for the first deploy and a recurring hour for maintenance. Model access currently runs through OpenRouter, so your code leaves the box in the request. That still beats a hosted reviewer for data-residency rules, and native Anthropic, OpenAI, Google Vertex, Ollama, and vLLM adapters are on the roadmap — the Ollama and vLLM ones matter most, since they'd keep everything in-house. Cost is worth sizing honestly. Mira is free, but a full-repo index plus agentic read_file and grep_repo calls on every PR burns tokens. v0.8.0's review.review_on_synchronize flag (default true) lets you stop reviewing every push to an open PR and only review on open or reopen — the first knob to turn if your bill surprises you. Use the .mira.yaml rules and the learning loop early. Teams that never encode conventions get a reviewer that argues with them; teams that reject comments and let
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Real-world workflow fit
Concrete scenarios for the personas Mira actually fits — and what changes day-one when you adopt it.
Deploy the Docker image on the company's own infrastructure, create the GitHub App with the documented permissions, generate the private key, set an OpenRouter key in the environment, and add per-repo rules in .mira.yaml.
Outcome: Every pull request gets inline comments and a walkthrough grounded in the indexed repository, with no source code leaving the company network and no per-seat fee.
Use the indexed org-wide package search after a disclosure, then rely on the layered security tier's review-time OSV checks when a PR adds or upgrades a dependency.
Outcome: You can name which repositories carry the affected package, and new risky dependencies get flagged at review time with a category-specific confidence floor.
Tune the confidence thresholds, set review.review_on_synchronize to false so only open/reopen triggers a review, and let the learning loop synthesize rules from comments marked as rejected.
Outcome: Fewer comments per PR, more of them worth reading, and rules that gradually match how your reviewers actually comment on merged PRs.
Use Cases
- Review every pull request with comments that account for your entire codebase, not just the diff.
- Enforce team coding standards with .mira.yaml rules that run automatically on new PRs.
- Answer which repositories are affected by a newly disclosed CVE using the indexed package search.
- Cut review cycle time by catching blockers and confidence-scored issues before human reviewers look.
- Improve review quality over time as Mira synthesizes rules from rejected comments and merged-PR behavior.
- Keep source code, diffs, and review data on-premises with a no-telemetry Docker deployment.
- Flag duplicate or overlapping open PRs before they cause merge conflicts.
Models Under the Hood
as of 2026-10-16
Limitations
- Mira is fully open-source and self-hosted: you deploy and maintain the single Docker image backed by SQLite or Postgres yourself, with no phone-home and no required telemetry by default.
- Supported git providers today are GitHub, GitLab, and Forgejo (including Codeberg) — a Bitbucket adapter is described as coming soon and is not usable now.
- Direct LLM backends such as Anthropic, OpenAI, Google Vertex, Ollama, and vLLM are documented as 'coming soon' rather than shipped, so the practical path today is routing through OpenRouter or using newer provider options like the Codex CLI provider.
- Review behavior — confidence thresholds, reasoning effort, security tiers, and per-PR comment caps — is configured via mira.yaml or environment variables, so setup presumes comfort editing deployment config.
as of 2026-10-04
Verification history
We have re-verified Mira 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Mira tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Self-Hosted (Apache 2.0)
$0/mo
Ideal for
Any engineering team that can run one Docker container and hold its own LLM API key — from a solo developer to a regulated org that must keep code on-premises.
What this tier adds
Starting and only tier: the full review engine, codebase indexing, security scan, dashboard, and learning loop, with no license key and no seat pricing.
Where the pricing makes sense
The company stage and team size where Mira's pricing actually pencils out — and where peers do it cheaper.
Mira is free under Apache 2.0 — no license key, no seat pricing, no paid tier. Your only recurring cost is the LLM provider bill. Against hosted reviewers like CodeRabbit that charge per seat per month, Mira scales down to zero software cost for a small team and scales up without a per-head multiplier for a large one. The crossover favors Mira when headcount grows, and favors hosted services when nobody on the team wants to run the container.
Setup time & first value
How long it actually takes to get something useful out of Mira — broken out by persona, not the marketing-page minute.
Per the vendor docs, deploy Mira and review your first PR in under 10 minutes for the happy path. Realistically: a solo developer with Docker experience should reach first value in under an hour; a platform engineer wiring a GitHub App plus OpenRouter key plus .mira.yaml rules across several repos should budget half a day; a regulated team adding secret management, Postgres, and a reverse proxy
Switching to or from Mira
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From CodeRabbit: deploy the Docker image, connect the same GitHub App permissions, then port recurring review preferences into .mira.yaml rules.
- →From GitHub Copilot code review: keep GitHub as the host, point Mira at your LLM key, and move repo-specific standards from reviewer habits into .mira.yaml.
- →From a diff-only bot: connect the host, let the indexer run across your repositories, then enable the layered security tier for added or upgraded dependencies.
- →From manual-only review: start with default rules on one high-traffic repo, watch a week of comments, then set confidence thresholds to match your tolerance.
- ↗To a hosted reviewer: disable the GitHub App or webhook, remove the .mira.yaml files from your default branch, and let a managed service take over the PR queue.
- ↗To GitHub Copilot code review: uninstall the app, delete the deployment and its database, and cancel the LLM provider key you were using for Mira.
- ↗To another self-hosted reviewer: export your .mira.yaml rules first, since those encode team standards that are not portable automatically.
Integrations
Resources & Guides
- Resourcedocs.miracode.ai
Home · Mira
Helpful link from docs.miracode.ai
- Documentationdocs.miracode.ai
Docs · Mira
Full product docs from docs.miracode.ai
- Resourcedocs.miracode.ai
Changelog · Mira
Helpful link from docs.miracode.ai
- Resourcedocs.miracode.ai
Release Notes · Mira
Helpful link from docs.miracode.ai
Tutorials & Learning
YouTube returned 6 videos for “Mira”, and we withheld 6: 6 could not be judged, because “Mira” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Mira.
Official links
Tools that pair well with Mira
Common stack mates teams adopt alongside Mira, with the specific reason each pairing earns its keep.
GitHub Copilot
GitHub Copilot is an AI coding agent that completes code, reviews pull requests, and runs tasks from issue to merge.
Sourcery
Sourcery is AI code review and security scanning that reviews every pull request and catches security issues in your diff and across your
Continue
Open-source AI coding agent for VS Code and JetBrains — free to fork since Cursor acquired Continue in January 2026.
Featured Head-to-Head Comparisons
Mira vs Spider Cloud
These tools serve completely different functions: Mira is for AI-powered code review on GitHub (self-hosted, free), while Spider Cloud is for web crawling and scraping (SaaS API, freemium). Choose Mira if you need automated PR review with full control over data and privacy; choose Spider Cloud if you're building AI agents or RAG systems that need fresh web content. They are not direct competitors but complementary tools for different stages of development.
Mira vs Voyage Ai
Choose Voyage AI if your priority is building a high-accuracy RAG pipeline with domain-specialized embeddings and rerankers, and you have budget for enterprise pricing. Choose Mira if you need a free, self-hosted AI code reviewer with full privacy, customizable rules, and the flexibility to use any LLM. They solve entirely different problems, so your decision hinges on whether you need retrieval or code review.
Mira vs Temporal Ai
If you need to build fault-tolerant, long-running AI agents or microservices that survive crashes and retries, Temporal is the clear choice. If your pain point is manual code review and you want a self-hosted, cost-effective AI reviewer that learns your team's rules, Mira is a fantastic pick. They solve completely different problems — pick based on whether you're orchestrating durable workflows or reviewing pull requests.
Alternatives to Mira
View allGitHub Copilot
GitHub Copilot is an AI coding agent that completes code, reviews pull requests, and runs tasks from issue to merge.
Frequently Asked Questions
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