Code2Prompt

About Code2Prompt

Code2Prompt is a context-engineering tool that ingests a directory and turns it into a structured, AI-ready prompt built around an explicit Goal + Format + Context framework. Rather than pasting files into a chat window and hoping the model infers what you want, you state the goal (what you are trying to achieve), the format (how the output should be structured), and let Code2Prompt supply the context as a source tree plus the contents of the files that matter. It uses glob patterns to include or exclude files, which is the operative feature: by keeping lockfiles, build output, and irrelevant directories out of the payload, you query the model with less noise, which the project argues directly reduces hallucination and improves performance. Although the name suggests code, the tool is directory-agnostic and the documentation demonstrates it equally on plain-text corpora — turning a folder of history notes into exam flashcards, or a recipes folder plus a pantry inventory into a cook-tonight recommendation — alongside the obvious software case of handing a Node app's source tree to a model and asking for a specific feature implementation. It ships in three flavours for three consumers: a CLI for humans generating prompts from the terminal, a Python SDK for programs that need to integrate prompt construction into larger automation, and an MCP server so agents can pull structured context themselves. Output is Markdown with fenced source blocks and a rendered tree, which pastes cleanly into any model interface.

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