Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/andreahaku/code-analysis-context-python-mcp/claude-mdgit clone --depth 1 https://github.com/andreahaku/code-analysis-context-python-mcpWhat 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 | $0.01830 | $0.01830 |
| Opus 5 | $0.00915 | $0.00915 |
| Sonnet 5 | $0.00366 | $0.00366 |
| Haiku 4.5 | $0.00183 | $0.00183 |
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 yesterday.
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.
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]
- Defines 6 Tool schemas with short parameter names (e.g.,
-
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
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.
- yesterday First seen · 212 lines · 1,830 tokens per session scan A 1a3c831b3725
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 10mo ago), licensed MIT. It adds 1,830 tokens to every session, about $0.0092 per session on Opus 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.
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