Octoparse MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Octoparse through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Octoparse, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Octoparse MCP Server
Connect your Octoparse framework to your AI agent and turn cloud-based web scraping into a fully conversational command center.
The Vercel AI SDK gives every Octoparse tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Task Execution — Trigger the launch engine using
start_taskwhenever data refresh is needed, or invokestop_taskto halt runaway crawlers instantly. - Status Monitoring — Keep a pulse on active bots by calling
get_task_status, or systematically drill down through your project taxonomy vialist_task_groupsandlist_tasks. - Data Ingestion — Dump the latest extracted web rows natively into the AI's context using
get_task_data, allowing the LLM to format, structure, or summarize the results immediately. - Token Operations — Authenticate dynamically utilizing
get_tokenwith your core credentials.
The Octoparse MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Octoparse to Vercel AI SDK via MCP
Follow these steps to integrate the Octoparse MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Octoparse and passes them to the LLM
Why Use Vercel AI SDK with the Octoparse MCP Server
Vercel AI SDK provides unique advantages when paired with Octoparse through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Octoparse integration everywhere
Built-in streaming UI primitives let you display Octoparse tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Octoparse + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Octoparse MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Octoparse in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Octoparse tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Octoparse capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Octoparse through natural language queries
Octoparse MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Octoparse to Vercel AI SDK via MCP:
clear_task_data
Done to purge testing footprints before production crawls. Delete all securely stored data for an Octoparse task
get_task_data
Use offset-based pagination strictly to prevent memory crash exceptions (max 1000 limit). Export un-exported data from a completed Octoparse scraping task
get_task_status
Get the current running status of an Octoparse cloud task
get_token
0 password grant. Returns an access_token. The access_token must be stored and reused for API calls until expiration. Obtain an OAuth 2.0 access token from Octoparse
list_task_groups
Use these IDs to filter executing scraping tasks nested inside a specific folder limit. List all task groups (folders) in the Octoparse account
list_tasks
Each task includes a taskId, status, and creation date. Use the taskId for starting or polling data. List all configured cloud scraping tasks on Octoparse
mark_data_exported
Execute this immediately after a successful `get_task_data`. Mark all currently stored data in an Octoparse task as extracted
start_task
Task changes status to Running instantly. Start a cloud scraping task on Octoparse
stop_task
Stop a running Octoparse cloud task
update_task_params
g. changing the core search URL or injected keywords) without opening the Octoparse IDE cleanly scaling parameterized bots. Dynamically update URL or parameter constraints driving a task
Example Prompts for Octoparse in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Octoparse immediately.
"Look up task 'LinkedIn Profiles Q4' and tell me how many rows it extracted."
"Start my Amazon Price Monitor crawler task now."
"Get the data extracted from task 'Real Estate NYC' and format it as a markdown table."
Troubleshooting Octoparse MCP Server with Vercel AI SDK
Common issues when connecting Octoparse to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpOctoparse + Vercel AI SDK FAQ
Common questions about integrating Octoparse MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Octoparse with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Octoparse to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.