Powered by MCP, CodeLlama-13B (local), Llama-3.1-8b-instant (cloud)
Modern PRs are huge—security issues or performance regressions slip through.
ReviewGenie does a 30-second AI review:
- Static regex rules → critical smells
- Local LLM → quick heuristics (no cloud cost)
- Cloud LLM → human-style summary & risk score
- Inline comments you can accept or ignore with one click
| Tool | Purpose | Typical latency |
|---|---|---|
ping |
Sanity check: show title/author/state | 0.3 s |
ingest |
Fetch diff JSON + SQLite cache | 1–2 s |
analyze |
Summary, smells[], rule_hits[], risk_score ∈ [0–1] | 6–10 s |
inline |
Posts or previews comments | 0.5 s |
check |
CI gate (risk_score > threshold) |
0.2 s |
generate_tests |
Stub pytest files + open PR | 4–6 s |
Privacy note: only the diff snippet is sent to Groq; full code never leaves your machine.
git clone https://github.com/mann-uofg/codeview-mcp.git
cd codeview-mcp
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
pip install -e .
# one-liner smoke
reviewgenie/codeview ping https://github.com/psf/requests/pull/6883Store secrets once (env-var OR keyring):
from codeview_mcp.secret import set_in_keyring
set_in_keyring("GH_TOKEN", "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") #GitHub PAT
set_in_keyring("OPENAI_API_KEY", "gsk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx") # Groq/OpenAI key
set_in_keyring("OPENAI_BASE_URL", "https://api.groq.com/openai/v1")Full tutorial: docs/QUICKSTART.md
- SQLite → diff cache (24 h)
- ChromaDB → hunk embeddings
- Back-off → GitHub retries (403/5xx)
- Tracing → OpenTelemetry spans
- Detailed diagram:
docs/ARCHITECTURE.md
See bench/benchmarks.md:
10 popular OSS PRs → avg ⏱ 8.1 s analyze, 💰 $0.0008 Groq cost, 96 % comment acceptance.
- API schema:
docs/API_SCHEMA.json - CLI reference:
docs/USAGE.md - Config & env:
docs/CONFIGURATION.md - Contributing:
docs/CONTRIBUTING.md
| Day | Highlight |
|---|---|
| 0 | Project skeleton, MCP “hello” |
| 1 | GitHub ingest + diff cache |
| 2 | Local LLM smells + cloud risk |
| 3 | Inline locator + ChromaDB |
| 4 | CLI wrapper + risk gate |
| 5 | Stub test generator |
| 6 | Vector de-dup fix, CI passing |
| 7 | bench.py: eval & markdown report |
| 8 | Secrets via keyring, back-off, OpenTelemetry |
| 9 | Full docs suite & OpenAPI schema |
Full changelog: docs/CHANGELOG.md
- 🚦 Live GitHub Action auto-labels “High-Risk” PRs
- 🖼 Web UI with trace explorer
- 🐳 (Optional) Docker image for k8s / GHCR
- 🕵️♂️ Multi-language support (Go, Rust)
Star the repo ⭐ & drop an issue if you’d like to help!