rig vs agentskit

Rust LLM application building blocks compared with JS agent tools

rig provides Rust building blocks for LLM applications, including shared interfaces for providers, vector stores, and agent workflows. agentskit is a TypeScript toolkit focused on assembling JavaScript agents from packages for models, tools, memory, retrieval, and interfaces.

rigagentskit
LanguageRustTypeScript
LicenseMITMIT
Stars8.8k34
Forks9893
Last analyzedOct 3, 2026Oct 4, 2026

Key differences

  • rig is written in Rust, while agentskit is written in TypeScript for JavaScript and TypeScript projects.
  • rig covers completion, embedding, transcription, and audio and image generation capabilities alongside agent workflows; agentskit centers on agent runtime, tools, memory, retrieval, and user interfaces.
  • rig offers interfaces for more than 20 model providers and more than 10 vector store integrations; agentskit provides provider adapters and packages that can be adopted individually or assembled into a broader stack.
  • rig separates portable core contracts from agent orchestration and supports its portable core and classic runtime in browser WASM; agentskit offers headless runtime options as well as React and terminal interfaces, with additional UI bindings.
  • rig warns that upcoming changes may be breaking; agentskit identifies its core package as stable and the rest of its independently progressing ecosystem as beta.
  • Both projects use the MIT license. rig has 8.8k stars and 989 forks, while agentskit has 34 stars and 3 forks.

Choose rig if you…

  • build LLM features in Rust and want provider integrations behind shared interfaces.
  • need completion, embedding, or supported audio and image capabilities alongside agent workflows.
  • want vector store integrations or portable core components, including browser-WASM support within its stated limits.
Read the rig analysis →

Choose agentskit if you…

  • build JavaScript or TypeScript agents that combine models, tools, memory, and retrieval.
  • want React or terminal interfaces, or prefer a headless agent runtime with packages you can adopt individually.
  • need agent features such as delegation, skills, MCP tools, or UI bindings across several JavaScript frameworks.
Read the agentskit analysis →

Compare the numbers side by side, or add more projects

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.