analyze-codebase-for-mcp

# Analyze Codebase for MCP Scan a codebase to discover functions, REST endpoints, CLI commands, and data access patterns that are good candidates for MCP tool exposure, then produce a structured tool specification document. ## When to Use - Planning an MCP server for an existing project and need to know what to expose - Auditing a codebase before wrapping it as an AI-accessible tool surface - Comparing what a codebase can do versus what is already exposed via MCP - Generating a tool specification document to hand off to `scaffold-mcp-server` - Evaluating whether a third-party library is worth wrapping as MCP tools ## Inputs - **Required**: Path to the codebase root directory - **Required**: Target language(s) of the codebase (e.g., TypeScript, Python, R, Go) - **Optional**: Existing MCP server code to compare against (gap analysis) - **Optional**: Domain focus (e.g., "data analysis", "file operations", "API integration") - **Optional**: Maximum number of tools to recommend (default: 20) ## Procedure ### Step 1: Scan Codebase Structure 1.1. Use `Glob` to map the directory tree, focusing on source directories: - `src/**/*.{ts,js,py,R,go,rs}` for source files - `**/routes/**`, `**/api/**`, `**/controllers/**` for endpoint definitions - `**/cli/**`, `**/commands/**` for CLI entry points - `**/package.json`, `**/setup.py`, `**/DESCRIPTION` for dependency metadata 1.2. Categorize files by role: - **Entry points**: main files, route handlers, CLI commands ...