7 Best llm.ts Alternatives in 2026 (Open Source)
llm.ts — Call any LLM with a single API. Zero dependencies.. vs Vercel AI SDK / LangChain.js: zero-dependency TypeScript library under 10kB that sends prompts to 30+ models from 3 providers in a single call — optimized for lightweight multi-model comparison
These 7 open-source tools do the same job. They are ordered by how closely they match llm.ts, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| llm.ts(original) | 213 | +-0 | 2023-05-09 |
| AI SDK | 27.1k | +644 | 2026-09-30 |
| LangChain | 18.2k | +143 | 2026-09-29 |
| Mastra | 28.5k | +972 | 2026-09-30 |
| voltagent | 10.7k | +587 | 2026-09-28 |
| rigging | 418 | +2 | 2026-09-29 |
| MiniChain | 1.2k | +-0 | 2023-12-07 |
| MCP TypeScript SDK | 13.5k | +237 | 2026-09-30 |
1. AI SDK
The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents
What sets it apart: Best-in-class TypeScript AI SDK with native UI hooks and Vercel integration — the React/Next.js standard for AI apps, unlike LangChain's Python-first approach
Best for: Full-stack TypeScript AI applications with React/Next.js; Building chatbots and generative UI with streaming
2. LangChain
The agent engineering platform
What sets it apart: vs LlamaIndex.TS: broader agent/chain abstractions and larger integration ecosystem; vs AI SDK: more opinionated with built-in chain patterns and LangSmith observability
Best for: Building LLM-powered apps in TypeScript/JavaScript; Rapid prototyping with multiple LLM providers; RAG applications with diverse data sources
3. Mastra
From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.
What sets it apart: Unlike LangChain (Python-first, complex abstraction) or CrewAI (Python multi-agent), Mastra is purpose-built for TypeScript with native Next.js/React integration, graph-based workflows with .then()/.branch()/.parallel() syntax, and built-in evals — making it the most natural choice for JS/TS production agent development.
Best for: TypeScript/Node.js teams building production AI agents with React/Next.js frontends; Developers who want agent workflows with human-in-the-loop approval built into their existing JS stack
4. voltagent
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
What sets it apart: Full-stack TypeScript agent platform with built-in workflow engine, voice support, and observability console — more opinionated than Vercel AI SDK, more TypeScript-native than LangChain
Best for: TypeScript developers building production agent systems with observability; Multi-agent systems with workflow orchestration and voice capabilities
5. rigging
Lightweight LLM Interaction Framework
What sets it apart: Unlike heavyweight frameworks like LangChain, Rigging combines Pydantic structured parsing with unstructured text seamlessly, using LiteLLM connection strings for zero-config model switching — designed for production simplicity over framework complexity
Best for: Python developers building production LLM applications who want structured outputs with minimal boilerplate; Security researchers at Dreadnode using LLMs for red-teaming and adversarial testing
6. MiniChain
A tiny library for coding with large language models.
What sets it apart: vs LangChain / LlamaIndex: extremely smaller and simpler — core prompt chaining with typed validation and Gradio visualization, without the complexity of full agent frameworks
Best for: Retrieval-augmented QA and multi-turn chat; Chain-of-thought reasoning pipelines; Developers wanting minimal LLM abstractions without framework bloat
7. MCP TypeScript SDK
The official TypeScript SDK for Model Context Protocol servers and clients
What sets it apart: The official reference TypeScript implementation of MCP — ensures full spec compliance and first-party support vs community implementations
Best for: Building MCP-compatible tools and servers in TypeScript; Exposing data sources and tools to LLM applications via standard protocol