Repo Prompt is a macOS native context engineering toolbox that helps AI models understand your codebase without wasting tokens on irrelevant code. The app automates assembling the perfect context for your project, allowing developers to build powerful AI prompts themselves or let AI agents use it via MCP.
The product offers smart file selection with visual file tree and instant preview, powerful search, and multi-repository support. Codemaps provide structural summaries that capture function signatures, types, and API contracts with 90% fewer tokens. Context Builder automatically discovers relevant files by understanding your codebase structure. Universal compatibility allows copying to clipboard for ChatGPT, Claude, Gemini, or connecting agents directly via MCP.
The app includes Repo Bench for measuring AI coding performance with data-driven rankings that assess large context reasoning, file editing precision, and instruction adherence. MCP Server Integration enables context syncing between AI tools and supercharges editors like Cursor with Repo Prompt's intelligence. The system maintains persistent context sync across all AI tools and enables agent-to-agent collaboration.
Benefits include 10x faster context building, 80% less token usage, and 100% local and private operation. Users can work with existing AI subscriptions like Claude MAX, ChatGPT Plus, and Gemini without extra API costs. The tool provides intelligent code mapping that reduces tokens and improves AI understanding of codebases.
The product targets developers working with AI coding assistants, particularly those using Claude Code, Cursor, and Codex. It integrates with MCP protocol and supports 15+ tools with standard protocol compatibility. The app works with local and hosted models including OpenAI, Anthropic, Gemini, DeepSeek, Azure, and OpenRouter.
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Repo Prompt targets developers working with AI coding assistants, particularly those using Claude Code, Cursor, and Codex. The product serves developers who need to optimize AI context usage and reduce token consumption while maintaining codebase understanding. It's designed for individuals and teams seeking to enhance their AI-assisted development workflow through efficient context engineering and seamless tool integration.