​
TS Tool Usage

Agentic clients like WeatherClient can be used as normal TS classes:

import { WeatherClient } from '@agentic/stdlib'

// Requires `process.env.WEATHER_API_KEY` (free from weatherapi.com)
const weather = new WeatherClient()

const result = await weather.getCurrentWeather({
  q: 'San Francisco'
})
console.log(result)

​
LLM Tool Usage

Or you can use these clients as LLM-based tools where the LLM decides when and how to invoke the underlying functions for you.

This works across all of the major AI SDKs via adapters. Here’s an example using Vercel’s AI SDK:

// sdk-specific imports
import { openai } from '@ai-sdk/openai'
import { generateText } from 'ai'
import { createAISDKTools } from '@agentic/ai-sdk'

// sdk-agnostic imports
import { WeatherClient } from '@agentic/stdlib'

const weather = new WeatherClient()

const result = await generateText({
  model: openai('gpt-4o-mini'),
  // this is the key line which uses the `@agentic/ai-sdk` adapter
  tools: createAISDKTools(weather),
  toolChoice: 'required',
  prompt: 'What is the weather in San Francisco?'
})

console.log(result.toolResults[0])

You can use our standard library of thoroughly tested AI functions with your favorite AI SDK – without having to write any glue code!

​
Multiple Tool Usage via AIFunctionLike

Here’s a slightly more complex example which uses multiple clients and selects a subset of their functions using the AIFunctionSet.pick method:

// sdk-specific imports
import { ChatModel, createAIRunner } from '@dexaai/dexter'
import { createDexterFunctions } from '@agentic/dexter'

// sdk-agnostic imports
import { PerigonClient, SerperClient } from '@agentic/stdlib'

async function main() {
  // Perigon is a news API and Serper is a Google search API
  const perigon = new PerigonClient()
  const serper = new SerperClient()

  const runner = createAIRunner({
    chatModel: new ChatModel({
      params: { model: 'gpt-4o-mini', temperature: 0 }
    }),
    functions: createDexterFunctions(
      perigon.functions.pick('search_news_stories'),
      serper
    ),
    systemMessage: 'You are a helpful assistant. Be as concise as possible.'
  })

  const result = await runner(
    'Summarize the latest news stories about the upcoming US election.'
  )
  console.log(result)
}

Here we’ve exposed 2 functions to the LLM, search_news_stories (which comes from the PerigonClient.searchStories method) and serper_google_search (which implicitly comes from the SerperClient.search method).

All of the SDK adapters like createDexterFunctions accept very flexible AIFunctionLike objects, which include:

  • AIFunctionSet - Sets of AI functions (like perigon.functions.pick('search_news_stories') or perigon.functions or serper.functions)
  • AIFunctionsProvider - Client classes which expose an AIFunctionSet via the .functions property (like perigon or serper)
  • AIFunction - Individual functions (like perigon.functions.get('search_news_stories') or serper.functions.get('serper_google_search') or AI functions created directly via the createAIFunction utility function)

You can pass as many of these AIFunctionLike objects as you’d like and you can manipulate them as AIFunctionSet sets via .pick, .omit, .get, .map, etc.

​
AI SDKs

Vercel AI SDK

Using Agentic with the Vercel AI SDK.

Mastra

Using Agentic with Mastra.

LangChain

Using Agentic with LangChain.

LlamaIndex

Using Agentic with LlamaIndex.

Firebase Genkit

Using Agentic with Genkit.

Dexa Dexter

Using Agentic with Dexter.

OpenAI

Using Agentic with OpenAI directly.

xsAI SDK

Using Agentic with the xsAI SDK.