CodeView MCP 🪄

Created By

mann-uofg7 months ago

AI-powered code-review toolkit: MCP server + CLI to analyze GitHub PRs with local LLM smells, cloud LLM summaries, inline comments, risk gating, and test stub generation.

# codeview

# code-review

Overview Content Tools Comments

Content

CodeView MCP 🪄

Powered by MCP, CodeLlama-13B (local), Llama-3.1-8b-instant (cloud)

1 Why

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

2 What it does

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.

3 Quick Start (5 min)

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/6883

Store 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

4 Architecture

pipeline

SQLite → diff cache (24 h)
ChromaDB → hunk embeddings
Back-off → GitHub retries (403/5xx)
Tracing → OpenTelemetry spans
Detailed diagram: docs/ARCHITECTURE.md

5 Benchmark

See bench/benchmarks.md: 10 popular OSS PRs → avg ⏱ 8.1 s analyze, 💰 $0.0008 Groq cost, 96 % comment acceptance.

6 Docs

API schema: docs/API_SCHEMA.json
CLI reference: docs/USAGE.md
Config & env: docs/CONFIGURATION.md
Contributing: docs/CONTRIBUTING.md

7 Day-by-Day Log

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