AI SDK: review, pricing, security and alternatives

What AI SDK does

AI SDK belongs to the frameworks family: libraries for building your own agents in code: loop, tools, memory, orchestration. On our grid it ranks #18 of the 28 projects of this family listed in the directory.

A framework is not used as is: it is a library developers build into their own code to describe the agent's tools, decision loop and memory. It requires programming skills, but leaves control over every detail.

You use it from: developer SDK. Usable models: Claude (Anthropic), GPT (OpenAI), Gemini (Google), DeepSeek, Mistral, local models (Ollama, llama.cpp, vLLM…), OpenRouter, and any OpenAI-compatible model. It can run on your own machine or server.

Who is AI SDK for?

It is for developers building their own agent or adding agentic AI to a product. Typical tasks people give it:

• build a business agent wired to your APIs
• orchestrate tool and model calls
• add memory and error recovery to an agent

It is a good candidate if your data must stay on your machines and you want the option of a local model, with no API fees.

Access and human control

A framework has no access of its own: the tools you plug in define what the agent can do. Start with read-only tools.

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

AI SDK pricing

The code is public but the repository declares no licence: reuse is not formally allowed. The real cost comes from model calls: each loop step sends the whole context back to the model, and a task of several dozen steps can cost far more than a single question. The LLM price calculator estimates it for the chosen model.

Getting started with AI SDK

1. Install it: the project ships as a Node.js package (install with npm, or run directly with npx). The exact command is in the repository README.
2. Pick the model: an API key from a provider, or a local model if your machine has enough graphics memory (the VRAM calculator tells you).
3. Start with the minimal example from the docs, then add one tool at a time and check what the agent does with it.
4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

A framework does not protect you by default: approval, minimal rights and sandboxing are up to you.

Points found for AI SDK:

• No licence: legally shaky for company use.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on May 23, 2023, the vercel/ai repository has 27,493 stars, 5,427 forks and 497 open issues, with 9,267 commits in total. It received changes this month.

31,261 releases in total; 30 in the last twelve months. Latest release: ai@7.0.153, on October 24, 2026.

AI SDK vs other frameworks

GitHub stars of the best-rated open-source projects in the frameworks family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

AI SDK and other frameworks at a glance

The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

How we rated it

Score: 69/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 29/40: 27,493 stars on a log scale (40 points from about 200,000).
• Activity 25/30: last commit less than a month ago, 30 releases in six months.
• Framework 15/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.