automation

rig – Scalable LLM Apps in Rust (8.8k+ stars)

For founders building AI products, rig lets you create modular, high‑performance LLM services in Rust, speeding development and simplifying scaling.

From the repo · “⚙️🦀 Build modular and scalable LLM Applications in Rust”

8,954 stars+63★ this week994 forksRustGuide quality 8/10 · reviewed Oct 9Updated 10/23/2026100% free · open source
What it does

Rig is a tool for building modular and scalable Large Language Model (LLM) applications in Rust, allowing founders to create custom AI-powered solutions.

When to use it
  • •When you need to integrate LLMs into a Rust-based application
  • •When you want to build a scalable and modular AI-powered system
  • •When you require a high degree of customization and control over your LLM application
Ready-to-paste prompt
cargo run --example my_rig_app --features default
Heads up: Make sure you have the latest version of Rust (1.64 or higher) installed, as rig relies on newer language features and dependencies
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🛠️ Technical setup

Expect 20–40 minutes in a terminal — or let your AI agent drive it.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/rig && curl -fsSL https://workflowstacks.com/api/skills/rig/claude-skill -o ~/.claude/skills/rig/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How rig – Scalable LLM Apps in Rust (8.8k+ stars) works
Codeflow
Free to inspect

Rig – Scalable LLM Apps in Rust (8.8k+ stars) is a very large Rust project (~196k lines across 660 code files, plus 712 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, MIT license, has a test suite.

Size
Very large codebase
~196k lines · 660 code files · days to read — use, don't read
Setup
Developer setup
A real software project. Use it via its install path; don't expect to read it all.
Runs on
Rust
No API keys detected
Rust 100%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    Cargo.toml
    Dependencies and the commands it exposes
  4. 4
    src/lib.rs
    Inside src/ — the main logic begins here
  5. 5
    examples/README.md
    A worked example — copy this to get going
What's in each folder
src/Core code — the actual logic1 files
examples/Examples you can copy152 files
crates/Folder761 files
scripts/Helper scripts4 files
xtask/Folder4 files
tests/Tests — proof it works2699 files
.github/CI / automation (GitHub Actions)15 files
img/Images & static assets9 files
READMEHas testsDocumentedCI checksExamples includedMIT licenseUpdated this month
Quick Actions
Details
Creator
0xPlaygrounds
Language
Rust
Category
automation
Published
6/5/2024

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Featured on WorkflowStacks
[![Featured on WorkflowStacks](https://workflowstacks.com/api/badge/rig.svg)](https://workflowstacks.com/skills/rig?utm_source=github&utm_medium=badge)
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