code2prompt

App Listed

A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.

Checked · Sources

Downloads
2,317
Dependents
Not applicable
Stars
7,756
Forks
458
Contributors
36
Commits
712
Latest release
4.3.0 ·

About

From the project README ·

Convert your codebase into a single LLM prompt.

Website • Documentation • Discord


code2prompt demo

Flow Diagram

Code2Prompt is a powerful context engineering tool designed to ingest codebases and format them for Large Language Models. Whether you are manually copying context for ChatGPT, building AI agents via Python, or running a MCP server, Code2Prompt streamlines the context preparation process.

⚡ Quick Install

Cargo
cargo install code2prompt 

To enable optional Wayland support (e.g., for clipboard integration on Wayland-based systems), use the wayland feature flag:

cargo install --features wayland code2prompt
Homebrew
brew install code2prompt
SDK with pip 🐍
pip install code2prompt-rs

🚀 Quick Start

Once installed, generating a prompt from your codebase is as simple as pointing the tool to your directory.

Basic Usage: Generate a prompt from the current directory. Output goes to stdout by default; use -c to copy it to the clipboard.

code2prompt .

Save to file:

code2prompt path/to/project --output-file prompt.txt

🤖 Agent Skill

Teach your coding agent to install and use code2prompt for repository navigation and scoped context gathering with the Skills CLI:

npx skills add mufeedvh/code2prompt
Read the full README

The code2prompt skill helps agents reduce exploration round trips: inspect a compact map of functions and classes using sem-core, then read relevant source files and tests together. It includes a map template and installation instructions for the optional entity-map feature, with a directory map fallback for standard builds. The code2prompt CLI is installed separately.

The installer adds the skill folder and its template to your agent. It may clone the repository temporarily to retrieve them; the rest of the repository is not installed as part of the skill.

To install it globally for a specific agent, for example Codex:

npx skills add mufeedvh/code2prompt --skill code2prompt --agent codex --global

🌐 Ecosystem

Code2Prompt is more than just a CLI tool. It is a complete ecosystem for codebase context.

🧱 Core Library
💻 CLI Tool
🐍 Python SDK
🤖 MCP Server
The internal, high-speed library responsible for secure file traversal, respecting .gitignore rules, and structuring Git metadata.Designed for humans, featuring both a minimal CLI and an interactive TUI. Generate formatted prompts, track token usage, and outputs the result to your clipboard or stdout.Provides fast Python bindings to the Rust Core. Ideal for AI Agents, automation scripts, or deep integration into RAG pipelines. Available on PyPI.Run Code2Prompt as a local service, enabling agentic applications to read your local codebase efficiently without bloating your context window.

📚 Documentation

Check our online documentation for detailed instructions

✨ Features

Code2Prompt transforms your entire codebase into a well-structured prompt for large language models. Key features include:

  • Terminal User Interface (TUI): Interactive terminal interface for configuring and generating prompts
  • Smart Filtering: Include/exclude files using glob patterns and respect .gitignore rules
  • Flexible Templating: Customize prompts with Handlebars templates for different use cases
  • Automatic Code Processing: Convert codebases of any size into readable, formatted prompts
  • Token Estimates: Estimate prompt size using parallel per-file token counts and estimated template overhead, including optional line numbers. The full rendered prompt is not re-tokenized, and the estimate excludes the JSON output envelope.
  • Smart File Reading: Simplify reading various file formats for LLMs (CSV, Notebooks, JSONL, etc.)
  • Git Integration: Include diffs, logs, and branch comparisons in your prompts
  • Blazing Fast: Built in Rust for high performance and low resource usage

Stop manually copying files and formatting code for LLMs. Code2Prompt handles the tedious work so you can focus on getting insights and solutions from AI models.

Alternative Installation

Refer to the documentation for detailed installation instructions.

Binary releases

Download the latest binary for your OS from Releases.

Source build

Requires:

git clone https://github.com/mufeedvh/code2prompt.git
cd code2prompt/
cargo install --path crates/code2prompt

⭐ Star Gazing

📜 License

Licensed under the MIT License, see LICENSE for more information.

Liked the project?

If you liked the project and found it useful, please give it a :star: !

👥 Contribution

Ways to contribute:

  • Suggest a feature
  • Report a bug
  • Fix something and open a pull request
  • Help me document the code
  • Spread the word
Runs on
GPU support unknown
What shows it
  • no dependency or feature matches a backend row
Native code
Required
  • Binds native code: libgit2-sys, libz-sys
Python bindings
No Python binding crate found
License
MIT

Compare with similar projects

Order: strongest tier first, then most downloads, then name, with unmeasured values last. A library counts downloads over 30 days. An app counts binary downloads per release. An app with none counts its crate downloads over 30 days. ML Rust runs this catalogue, so its closest project always gets a row.

code2prompt beside the projects that share a topic with it
ProjectDownloadsDependentsStarsLatest releaseRuns on (GPU)Native codeLicense
code2prompt This page App Listed

A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.

2,317 binary downloads per release Not applicable 7,756 4.3.0 GPU support unknown Binds native code: libgit2-sys, libz-sys MIT
llmfit App Featured

Right-size LLM models to your system hardware. Interactive TUI and CLI to match models against available RAM, CPU, and GPU.

3,821 binary downloads per release Not applicable 38,787 1.1.20 Metal No native code found MIT
agent App Listed

Ship your code, on autopilot. An open source agent that lives on your machines 24/7 and keeps your apps running. 🦀

19,860 binary downloads per release Not applicable 1,859 0.3.88 GPU support unknown Binds native code: tree-sitter, tree-sitter-language, tikv-jemalloc-sys (feature jemalloc) Apache-2.0
lsp-ai App Listed Dormant

LSP-AI is an open-source language server that serves as a backend for AI-powered functionality, designed to assist and empower software engineers, not replace them.

2,314 binary downloads per release Not applicable 3,210 0.7.0 CUDA, Metal Binds native code: tree-sitter, tree-sitter-language, llama-cpp-sys-2 (feature cuda). Build uses a native toolchain: cc MIT
axp App Listed

An open protocol that gives AI agents a secure, sandboxed place to run code and use tools — with lean context usage. AXP works alongside MCP

Not measured Not applicable 3 Not measured Not measured Not measured Apache-2.0
rtk App New

Rust Token Killer - High-performance CLI proxy to minimize LLM token consumption

2,594 binary downloads per release Not applicable 85,939 0.42.4 GPU support unknown Binds native code: libsqlite3-sys Apache-2.0
tensorzero App Archived

TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.

35 downloads over 30 days Not applicable 11,705 0.0.0 GPU support unknown No native code found Apache-2.0
Why ListedNo archive, New or Featured rule places it, so it is Listed.

What it lacks for Featured

  • The check holds no value for Homebrew installs on request over 365 days, Repology repository families, Docker pull growth over 90 days. A gate that lacks its signal does not pass.

What else the check found

  • The last activity is on 3 Nov 2026, 6 days ago. The rules expect an update within 365 days. Dormancy rule

Not measured: Homebrew installs on request over 365 days, Repology repository families, Docker pull growth over 90 days.

Exact rules: Listed, Featured app. The check on applied thresholds version 9.

Every rule outcome, as the check records it
  • expected-interval: app: E = 365 days
  • dormancy: last activity 2026-11-03, 6 days ago, E = 365: active
  • featured: not featured: unknown homebrew_on_request_365d, repology_families, docker_pull_growth_90d
  • listed: listed: no archive, new or featured rule applies
Crates2 crates

Measurements and sources

Each signal row shows the raw value, its source and the fetch date. The Sources list gathers every distinct source on this page. Movement needs more history.

Sources6 sources
Adoption2,317 binary downloads per release4 not measured
Adoption measurements
SignalValueSourceFetchedCounts
Active dependentsNot measuredYes
New dependents (365 days)Not measuredYes
Peak active dependentsNot measuredYes
Active dependents as a share of the peakNot measuredYes
Binary downloads per release2317GitHub releasesYes
MaintenanceLatest human commit: 6 days ago4 not measured
Maintenance measurements
SignalValueSourceFetchedCounts
Latest human commit2026-11-03GitHub repositoryYes
Latest release2026-06-13crates.io database dumpYes
First release2024-03-11crates.io database dumpYes
Latest version4.3.0crates.io database dumpNo
Days the oldest outside issue waits for a reply482GitHub repositoryYes
Maintainer replies over 365 days17GitHub repositoryYes
Repository archivedfalseGitHub repositoryYes
Repository gonefalseGitHub repositoryYes
Release commit or manifest in the repotruecrates.io packageNo
Published docsNot measuredYes
Latest release fails cargo checkNot measuredYes
Build check dateNot measuredYes
Build check toolchainNot measuredYes
SecurityNot measured
Security measurements
SignalValueSourceFetchedCounts
Unpatched vulnerabilities past the grace windowNot measuredYes
RustSec unmaintained advisoryNot measuredYes
Deprecation noticeNot measuredYes
Deprecated requirementNot measuredYes
Distribution9 releases, 439 downloads over 30 days6 not measured
Distribution measurements
SignalValueSourceFetchedCounts
Releases9crates.io database dumpNo
Downloads over 30 days439crates.io database dumpNo
Binary downloads over the last 3 releases6952GitHub releasesYes
Homebrew installs on request over 365 daysNot measuredYes
Repology repository familiesNot measuredYes
Docker pull growth over 90 daysNot measuredYes
Docker pulls at the growth baselineNot measuredYes
Every version a prereleasefalsecrates.io database dumpYes
Every version 0.0.xfalsecrates.io database dumpYes
Every version yankedNot measuredYes
Crate deleted from crates.ioNot measuredYes
Repository7,756 stars, 458 forks, 36 contributors, 712 commits. Stars alone never qualify a project.
Repository measurements
SignalValueSourceFetchedCounts
GitHub stars7756GitHub repositoryYes — one part of the repository route
GitHub forks458GitHub repositoryYes — one part of the repository route
Contributors with a GitHub account36GitHub contributorsYes — one part of the repository route
Commits on the default branch712GitHub repositoryNo
Repository's main crate left out of the entrynonecrates.io database dumpYes
Facts that never count
Facts that never count measurements
SignalValueSourceFetchedCounts
LicenseMITcrates.io database dumpNo
Runs on, from listed crates and their direct dependenciesGPU support unknowncrates.io database dumpNo
What shows each backendno dependency or feature matches a backend rowcrates.io database dumpNo
Native code, from listed crates and their dependenciesBinds native code: libgit2-sys, libz-syscrates.io database dumpNo
Python bindings, from direct dependencies of listed cratesNo Python binding crate foundcrates.io database dumpNo
Crates that depend on a listed crate directlyNot measuredNo

Corrections and review history

Report a correction

No correction applies to this entry.

Judgments

A judgment enters only through an approved issue and a merged pull request.

No judgment applies to this entry.