ParseHub 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 ParseHub 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 ParseHub, 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 ParseHub MCP Server
Bring ParseHub Cloud Scraping directly into your AI workflows. Manage pre-configured web scraping targets natively and orchestrate complex headless browser automation directly from chat. Dispatch run jobs on command, query execution status limits, and extract final parsed payloads securely.
The Vercel AI SDK gives every ParseHub 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
- Project Navigation — Inspect and list configured ParseHub projects, determining start URLs, templates, and total crawler pages attached
- Execution Dispatch — Command remote servers to trigger specific headless data extraction jobs
run_projectoptionally overriding starting URLs natively - Observability Tracing — Monitor exactly where a
Runobject is (queued, initialized, running, complete) without checking the desktop app - Payload Extraction — Pull down structured arrays containing the scraped payloads securely via
get_run_datamatching explicit datasets
The ParseHub 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 ParseHub to Vercel AI SDK via MCP
Follow these steps to integrate the ParseHub 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 ParseHub and passes them to the LLM
Why Use Vercel AI SDK with the ParseHub MCP Server
Vercel AI SDK provides unique advantages when paired with ParseHub 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 ParseHub integration everywhere
Built-in streaming UI primitives let you display ParseHub 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
ParseHub + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the ParseHub MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query ParseHub in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate ParseHub tools and return structured JSON responses to any frontend
Chatbots with tool use: embed ParseHub capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with ParseHub through natural language queries
ParseHub MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect ParseHub to Vercel AI SDK via MCP:
cancel_run
If the run was already scraping pages, partial data may be available. Data from already-scraped pages is preserved and can be retrieved with get_run_data. Use this to stop long-running scrapes or free up queue slots. Cancel a queued or actively running ParseHub run
delete_run
Cannot be undone. Use this to clean up old runs and free up storage quota on your account. Permanently delete a ParseHub run and its extracted data
get_last_ready_data
Ideal for dashboards or integrations that always want the freshest available data without managing individual run tokens. Instantly get the latest completed data for a ParseHub project
get_project
The project_token can be found via list_projects or in the ParseHub desktop client settings tab. Get detailed configuration of a specific ParseHub project
get_run_data
Only works when the run status is "complete" and data_ready is true. The JSON structure mirrors the template selection configuration set up in the ParseHub desktop client. Download the raw JSON data extracted from a completed ParseHub run
get_run_details
Poll this endpoint to wait for a run to complete before fetching data. Check the status of a specific ParseHub run
list_projects
Each project includes a project_token (unique identifier), title, last_run timestamp, and template configuration. Use the project_token for all subsequent run management operations. List all ParseHub web scraping projects
list_runs
Useful for auditing or finding a specific completed run to fetch data from. Get the history of all runs for a ParseHub project
run_project
Returns a run_token for tracking progress. The run enters a queue and begins processing within seconds. Use get_run to monitor and get_run_data to retrieve results once complete. Start a new ParseHub scraping run for a project
run_project_with_url
Perfect for scraping different pages with the same template (e.g., different product categories). The template extraction rules still apply unchanged — only the starting page changes. Start a ParseHub run targeting a custom URL instead of the project default
Example Prompts for ParseHub in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with ParseHub immediately.
"Fetch the list of scrape projects I have on my ParseHub account."
"Start a new run for project 't9zx...' and check its status."
"Extract the finished data JSON payload from run ID 'run_k1l'."
Troubleshooting ParseHub MCP Server with Vercel AI SDK
Common issues when connecting ParseHub to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpParseHub + Vercel AI SDK FAQ
Common questions about integrating ParseHub 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 ParseHub 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.
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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 ParseHub to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.