AI SDLC Quality Gate MCP Server

This is a personal learning project for exploring Model Context Protocol (MCP), static code analysis, QA automation, and practical SDLC quality gates.

It is designed to be a small, local-first reference implementation that can be used from Cursor, Claude Desktop, or Claude Code while experimenting with developer workflow automation.

Tool Highlights

Tool	Outcome
`audit_code_quality`	Static Python/TypeScript security and reliability findings.
`generate_playwright_spec`	Executable async Playwright/Pytest test source.
`run_sdlc_healthcheck`	0-100 repository quality score and recommendations.

Quickstart

python -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt
python -m src.server
python -m pytest -q

Cursor and Claude Integration

Copy mcp_config.json into Cursor or Claude Desktop's mcpServers configuration and replace cwd with this repository's absolute path. Claude Code can use the same command: python -m src.server.

Screenshots / GIF Guide

After connecting the server, capture one successful interaction for each tool and save the assets under docs/assets/.

Safety Boundaries

The server performs local static analysis only. It does not execute target code, need credentials, call an LLM, or use a network API.

AI-SDLC-MCP-Server