What is code-analysis-context-python-mcp CLAUDE.md?

Project instructions for an MCP server that analyzes Python codebases, especially projects using tools such as pandas, NumPy, scikit-learn, FastAPI, and Django. MCP is a standard way for AI tools to use external tools.

For developing and validating the Python code-analysis server and testing its six analysis tools.

They tell an AI coding agent how the project works and how to install, run, test, format, lint, and type-check it.

How andreahaku/code-analysis-context-python-mcp configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to andreahaku/code-analysis-context-python-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/andreahaku/code-analysis-context-python-mcp/main/CLAUDE.md

Clone the repo

git clone --depth 1 https://github.com/andreahaku/code-analysis-context-python-mcp

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/andreahaku/code-analysis-context-python-mcp/claude-md/github.svg)](https://agentmods.dev/instructions/andreahaku/code-analysis-context-python-mcp/claude-md)

Your own site

<a href="https://agentmods.dev/instructions/andreahaku/code-analysis-context-python-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/andreahaku/code-analysis-context-python-mcp/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/andreahaku/code-analysis-context-python-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/andreahaku/code-analysis-context-python-mcp/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,830 This file is loaded in full into every session.

When invoked 1,830 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.01830	$0.01830
Opus 5.5	$0.00732	$0.00732
Sonnet 5.5	$0.00366	$0.00366
Haiku 4.5	$0.00183	$0.00183

Measured 2mo ago against content hash 1a3c831b3725, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-analysis-context-python-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 212 lines

How it starts

The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

This is an MCP (Model Context Protocol) server that provides deep codebase analysis for Python projects, specifically designed for data analysis engineers working with pandas, numpy, sklearn, fastapi, django, and other Python frameworks.

The server exposes 6 analysis tools via the MCP protocol. It's a complete, production-ready implementation with 3,787 lines of code across 18 modules.

Development Commands

Setup & Installation

# Development installation with all dependencies
pip install -e ".[dev]"

# Install only runtime dependencies
pip install -e .

Running & Testing

# Test the MCP server by analyzing itself
python3 test_tools.py

# Run the MCP server (for use with Claude Desktop or other MCP clients)
python3 -m src.server

# Or use the installed script
code-analysis-python-mcp

Code Quality

# Format code (100 char line length)
black src tests
isort src tests

# Linting
flake8 src tests

# Type checking (strict mode enabled in pyproject.toml)
mypy src

# Run tests with coverage
pytest --cov=src --cov-report=html --cov-report=term

Architecture Overview

High-Level Design

MCP Server Pattern: The architecture follows a clear separation between the MCP protocol layer and analysis logic:

src/server.py - MCP protocol handler (338 lines)
- Defines 6 Tool schemas with short parameter names (e.g., path, inc, exc)
- Maps short params to long params via map_params() function
- Routes tool calls to appropriate analyzers
- All tools are async functions returning Sequence[TextContent]
src/tools/ - 6 independent analysis tools (each ~300-500 LOC)
- Each tool is a standalone async function accepting a dict of long-form params
- Tools return JSON results wrapped in TextContent
- No shared state between tools
- Tools: architecture_analyzer.py, pattern_detector.py, dependency_mapper.py, coverage_analyzer.py, convention_validator.py, context_pack_generator.py

Read the full file on GitHub · 212 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 212 lines · 1,830 tokens per session scan A 1a3c831b3725

Subscribe to this mod's changes

code-analysis-context-python-mcp CLAUDE.md is an instructions file published in the GitHub repository andreahaku/code-analysis-context-python-mcp (1 stars, last pushed 1y ago), licensed MIT. It adds 1,830 tokens to every session, about $0.0073 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Debugging

code-analysis-context-python-mcp CLAUDE.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
code-analysis-context-python-mcp CLAUDE.mdandreahaku/code-analysis-context-python-mcp	Instructions file	1	1y ago	MIT	A	1,830	Claude Code
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

code-analysis-context-python-mcp: Instructions file for Claude Code