ctroy-code-analysis

Distributed via PyPI!

An MCP server that provides six code review tools for use with Claude Code (or any MCP client). Each reviewer reads a file from disk, pairs its contents with a structured review prompt, and returns the bundle for the LLM to evaluate.

Installation

pip install ctroy-code-analysis

Requires Python 3.10+.

Related MCP server: Claude Code Review MCP

Connecting to Claude Code

Add the server to your project's .mcp.json (per-project) or ~/.claude.json (global):

{
  "mcpServers": {
    "ctroy-code-analysis": {
      "command": "ctroy-code-analysis"
    }
  }
}

Restart Claude Code. The six tools will appear automatically.

Tools

Each tool takes a filepath (or directory), reads the contents, and returns them alongside review instructions. The LLM then generates the review.

Example usage in Claude Code

Ask Claude naturally:

Use review_comments on src/parser.py

Use review_performance on lib/data_pipeline.py

Use draw_gridmat on the src/ directory

Prompts

Each tool also has a corresponding prompt (prefixed with prompt_). Prompts return just the review instructions without reading any files, so the LLM applies them to code it already has in context.

What the reviewers look for

Comment review flags two categories, ordered by severity: inaccurate comments (say something the code doesn't do) and superfluous comments (restate what the code clearly says).

Name review flags five categories: unclear names, inaccurate names, shadowed variables, overloaded temporaries (tmp, i, x reused across unrelated blocks), and low-confidence blocks where names make it hard to reason about the code.

Cohesion review looks for ten patterns of scattered code: distant configuration, split validation, fragmented type definitions, separated tests, dispersed error handling, remote utilities, disconnected docs, scattered state management, split domain logic, and orphaned dependencies.

Performance review analyzes five categories: algorithmic complexity, data structure efficiency, unnecessary work, I/O and external operations, and language-specific optimizations. Each finding includes expected improvement and tradeoffs.

Test coverage review checks for gaps in: happy paths, branch coverage, edge cases, error paths, boundary conditions, integration points, return values, state changes, and concurrency concerns.

Gridmat picks up to 5 entry points, assigns each a color-coded emoji, and traces execution paths downward through the codebase in an ASCII box-drawing diagram.

Running the server directly

The server uses stdio transport. To start it manually:

ctroy-code-analysis

Or:

python -m ctroy_code_analysis.server