# How to Integrate Wigolo with Vercel AI SDK for Edge-Friendly Tool Usage

> Integrate Wigolo with Vercel AI SDK for edge-friendly tool usage. Run LLM-agnostic search fetch and extract operations efficiently on Vercel’s edge network.

- Repository: [Towhid Khan/wigolo](https://github.com/KnockOutEZ/wigolo)
- Tags: how-to-guide
- Published: 2026-07-19

---

**Wigolo provides LLM-agnostic tools that integrate with the Vercel AI SDK through a thin client wrapper, enabling search, fetch, and extract operations to run efficiently on Vercel's edge network without Node-specific dependencies.**

Wigolo is an open-source toolkit providing LLM-agnostic utilities for data acquisition and transformation. When you integrate wigolo with Vercel AI SDK for edge-friendly tool usage, you unlock low-latency AI tool execution on Vercel's Edge Network without the overhead of traditional server processes. The integration leverages pure async functions that bypass Node.js-specific APIs, making it ideal for lightweight edge deployments according to the KnockOutEZ/wigolo source code.

## Understanding the Integration Architecture

The integration between Wigolo and the Vercel AI SDK follows a three-layer architecture that separates tool logic from platform-specific adapters.

### Core Tool Implementations

The foundation resides in [`src/tools.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/tools.ts), which houses the pure async functions powering Wigolo's capabilities. These functions handle **search**, **fetch**, and **extract** operations using only web-standard APIs. Because they contain no Node-specific dependencies, they execute safely within Vercel's lightweight JavaScript edge runtime.

### The Client Wrapper

[`src/client.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/client.ts) imports the individual tool implementations and re-exports them under a unified `wigolo` object. This file creates the `createVercelTool` schema mapper, which transforms Wigolo's typed request/response shapes into the format expected by Vercel's AI SDK. The client serves as a façade that maintains type safety while adapting to platform conventions.

### Vercel SDK Glue Layer

The entry point at [`src/index.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/index.ts) exposes `createClient` and `run` utilities. The `createClient` function builds a Vercel-compatible `ToolDefinition` map from the Wigolo client, while the `run` helper executes selected tools and formats results for the edge runtime. This layer handles serialization and response streaming automatically.

## Step-by-Step Implementation Guide

Follow these steps to deploy Wigolo tools on Vercel's edge network.

### Install the Package

Add the Wigolo Vercel AI SDK package to your project:

```bash
npm i @wigolo/vercel-ai-sdk

```

### Create the Edge Function

Create a new route file at [`app/api/wigolo/route.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/app/api/wigolo/route.ts) (or your framework's equivalent). Import `createClient` and `run` from the package, then initialize the client with your preferred model configuration:

```typescript
import { createClient, run } from '@wigolo/vercel-ai-sdk';

const wigolo = createClient({ model: 'gpt-4o-mini' });

export const GET = async (req: Request) => {
  const url = new URL(req.url);
  const query = url.searchParams.get('q') ?? '';

  const result = await run(wigolo, 'search', { query });
  return new Response(JSON.stringify(result), { status: 200 });
};

```

### Execute Tools on the Edge

Invoke specific tools using the `run` helper with typed parameters:

- **Search**: `run(wigolo, 'search', { query })` returns ranked URLs
- **Fetch**: `run(wigolo, 'fetch', { url })` streams content with politeness checks
- **Extract**: `run(wigolo, 'extract', { url, selector })` returns DOM snippets

All calls return standardized response shapes defined in [`src/types.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/types.ts), ensuring consistency across different tool types.

## Practical Edge Function Examples

The repository includes working examples in [`examples/vercel-ai-sdk-tools/tools.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/examples/vercel-ai-sdk-tools/tools.ts) that demonstrate real-world usage patterns:

```typescript
import { createClient, run } from '@wigolo/vercel-ai-sdk';

const wigolo = createClient({ model: 'claude-3.5-sonnet' });

export async function edgeSearch(query: string) {
  return await run(wigolo, 'search', { query });
}

export async function edgeFetch(url: string) {
  return await run(wigolo, 'fetch', { url });
}

export async function edgeExtract(url: string, selector: string) {
  return await run(wigolo, 'extract', { url, selector });
}

```

These functions run directly on Vercel's edge nodes, minimizing latency by processing requests geographically close to users.

## Summary

- **Wigolo tools** in [`src/tools.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/tools.ts) provide pure async implementations of search, fetch, and extract operations without Node.js dependencies
- The **client wrapper** in [`src/client.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/client.ts) adapts these tools to Vercel AI SDK conventions through the `createVercelTool` schema
- **Entry point utilities** in [`src/index.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/index.ts) expose `createClient` and `run` for seamless edge deployment
- All tool executions occur on **Vercel's edge network**, eliminating cold starts and reducing latency compared to traditional serverless functions
- The integration maintains **type safety** through shared definitions in [`src/types.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/types.ts) while supporting multiple LLM providers

## Frequently Asked Questions

### What makes Wigolo compatible with Vercel's edge runtime?

Wigolo's tool implementations use only web-standard APIs and pure async functions without Node.js-specific modules like `fs` or `http`. This allows the code to execute on Vercel's lightweight JavaScript engine running on the Edge Network.

### How do I add custom tools to the Wigolo Vercel integration?

Add new tool implementations to [`src/tools.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/tools.ts) following the existing async function pattern, then register them in [`src/client.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/client.ts). The `createClient` function in [`src/index.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/src/index.ts) will automatically include them in the exported tool map without requiring changes to the edge function code.

### Can I use Wigolo with different LLM providers on Vercel?

Yes. The `createClient` function accepts a `model` parameter (e.g., `gpt-4o-mini` or `claude-3.5-sonnet`) that configures the client for your preferred provider. The tool implementations remain LLM-agnostic, while the Vercel AI SDK handles provider-specific formatting.

### Where can I find working examples of this integration?

Reference the [`examples/vercel-ai-sdk-tools/tools.ts`](https://github.com/KnockOutEZ/wigolo/blob/main/examples/vercel-ai-sdk-tools/tools.ts) file in the KnockOutEZ/wigolo repository for complete, copy-ready implementations of edge functions using search, fetch, and extract tools.