CodeView MCP 🪄
@mann-uofg
About CodeView MCP 🪄
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.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"codeview-mcp": {
"command": "python",
"args": [
"-m",
"venv",
".venv",
"&&",
"source",
".venv/bin/activate"
]
}
}
}Tools
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Overview
What is CodeView MCP 🪄?
CodeView MCP 🪄 is an MCP server that performs a 30-second AI review of pull requests, combining static regex rules for critical smells, a local LLM (CodeLlama-13B) for quick heuristics, and a cloud LLM (Llama-3.1-8b-instant via Groq/OpenAI) for human-style summaries and risk scores. It targets developers who need fast, privacy-conscious PR analysis.
How to use CodeView MCP 🪄?
Clone the repository, create a Python virtual environment, install dependencies, and install the package with pip install -e .. Run a smoke test with reviewgenie/codeview ping https://github.com/psf/requests/pull/6883. Store secrets such as a GitHub PAT and Groq/OpenAI API key using the codeview_mcp.secret keyring module.
Key features of CodeView MCP 🪄
- Static regex rules for critical code smells
- Local LLM heuristics with no cloud cost
- Cloud LLM human-style summary and risk score (0–1)
- One-click inline comment accept or ignore
- SQLite diff cache and ChromaDB hunk embeddings
- OpenTelemetry tracing and GitHub back-off logic
Use cases of CodeView MCP 🪄
- Reviewing large PRs quickly for security or performance issues
- Running a CI gate that blocks merges when risk score exceeds a threshold
- Generating stub test files and opening test PRs automatically
- Auditing code with inline comments that can be accepted or dismissed
FAQ from CodeView MCP 🪄
What does the analyze tool produce?
It returns a summary, a list of smells, rule hits, and a risk score between 0 and 1, with typical latency of 6–10 seconds.
How does CodeView MCP 🪄 protect code privacy?
Only the diff snippet is sent to the cloud LLM (Groq); the full codebase never leaves your machine.
What LLMs does CodeView MCP 🪄 use?
It uses CodeLlama-13B locally and Llama-3.1-8b-instant via a cloud provider (Groq or OpenAI, configured via OPENAI_API_KEY and OPENAI_BASE_URL).
What are the runtime dependencies?
Python 3.10+, SQLite, ChromaDB, and network access for cloud LLM calls. Secrets are stored via the system keyring.
How is the server invoked or transported?
The README shows a CLI command (reviewgenie/codeview) and smoke test; the MCP transport is not specified further.
Frequently asked questions
What does the `analyze` tool produce?
It returns a summary, a list of smells, rule hits, and a risk score between 0 and 1, with typical latency of 6–10 seconds.
How does CodeView MCP 🪄 protect code privacy?
Only the diff snippet is sent to the cloud LLM (Groq); the full codebase never leaves your machine.
What LLMs does CodeView MCP 🪄 use?
It uses CodeLlama-13B locally and Llama-3.1-8b-instant via a cloud provider (Groq or OpenAI, configured via `OPENAI_API_KEY` and `OPENAI_BASE_URL`).
What are the runtime dependencies?
Python 3.10+, SQLite, ChromaDB, and network access for cloud LLM calls. Secrets are stored via the system keyring.
How is the server invoked or transported?
The README shows a CLI command (`reviewgenie/codeview`) and smoke test; the MCP transport is not specified further.
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