zlm-v1-iab-classify-edge model with Claude entirely inside Claude Desktop, with no code to write or run. You connect the hosted ZeroGPU MCP server once, then Claude reads your article, calls the IAB classifier as a tool to get hard signals (IAB content categories, audience segments, and confidence scores), and uses those signals to write an Ad Brief, a Newsletter Blurb, and a Content Pitch, each in a distinct voice. By pairing ZeroGPU’s edge classifier with Claude’s writing, this guide walks you through a transparent, reproducible pipeline where the classification numbers visibly drive every line of copy, all from a chat window.
For the full reference, see the zlm-v1-iab-classify-edge model card and the ZeroGPU MCP server guide.
In this guide, you’ll explore:
- ZeroGPU IAB Classifier (
zlm-v1-iab-classify-edge): An edge-served model that maps any text straight to the IAB Content Taxonomy, returning content categories, audience segments, and a per-label confidence score in a single call. No instructions or prompt engineering needed, you send text and get structured signals back. See the model card. - ZeroGPU MCP Server: The hosted Model Context Protocol server at
https://mcp.zerogpu.ai/mcpthat exposes ZeroGPU’s edge models, including the IAB classifier aszerogpu_classify_iab, as MCP tools any client can call. Connect it once and Claude Desktop can reach the classifier directly. See the MCP server guide. - ZeroGPU: An ultra-fast, compute-efficient inference provider for apps and agents. We run purpose-built small and nano language models across an edge-powered network for the high-volume, purpose-specific tasks your app or agent runs constantly. Plug in our OpenAI-compatible API and you’re live - zero GPU infrastructure, serverless, auto-scaling by default.
- Claude Desktop: Anthropic’s desktop app for Claude. Here it orchestrates the pipeline: it connects to the ZeroGPU MCP server, calls the classifier as a tool, reads the returned IAB categories, audience segments, and confidence scores, and writes three distinct outputs grounded in those numbers.
🎥 Watch the Video Guide
Prefer a quick walkthrough? Watch the full demo here:🔑 Get Your ZeroGPU API Key
You’ll need a ZeroGPU API key and Project ID so Claude Desktop can authenticate to the MCP server. This is the only credential setup required, there are no packages to install and no keys to paste into code. You can go to here to get an API key and Project ID from ZeroGPU. The key starts withzgpu-api- and the Project ID (UUID) is on the project settings page.
- Sign in to the ZeroGPU dashboard.
- Open API Keys and click Create key.
- Copy the key (starts with
zgpu-api-) and grab your Project ID (UUID) from the project settings page.
🔌 Connect the ZeroGPU MCP Server in Claude Desktop
The ZeroGPU MCP server is hosted athttps://mcp.zerogpu.ai/mcp and authenticates with two headers on every request: x-api-key (your API key) and x-project-id (your Project ID). To make its tools available to Claude, add the server to Claude Desktop’s MCP configuration.
In Claude Desktop, open Settings → Developer → Edit Config, then add the zerogpu entry to mcpServers (substitute your real key and Project ID):
zerogpu_classify_iab) appear in the tools menu of any chat, and Claude can call them on its own. For the request and response shape behind the tool, see the model card; for the full tool catalog, see the MCP server guide.
🏷️ Classify Content with the ZeroGPU MCP Server
ZeroGPU is an ultra-fast, compute-efficient inference provider for apps and agents. We run purpose-built small and nano language models across an edge-powered network for the high-volume, purpose-specific tasks your app or agent runs constantly. Plug in our OpenAI-compatible API and you’re live - zero GPU infrastructure, serverless, auto-scaling by default. In this section, we will classify a short snippet of content against the IAB Content Taxonomy as a standalone example, straight from the Claude Desktop chat.zlm-v1-iab-classify-edge maps your input directly to the taxonomy, so you only send text and get back audience segments and content categories (in both iab_1_0 and iab_2_2 versions), each with a confidence score. To try it, just ask Claude to classify a sentence:
zerogpu_classify_iab tool and calls it with your text:
🎯 Turn One Article into Three Targeted Outputs
This section hands Claude a full article and one plain prompt, lets it call the ZeroGPU classifier as a tool, and turns the returned signals into three clearly different pieces of copy. For the classifier to be more than decoration, Claude has to actually call it and then let the numbers steer the writing. The cleanest way to lock that behavior in is a Claude Desktop Project: create one and paste the following into its custom instructions, so every chat in the project follows the same steps.[article text] and Claude does the rest.
zerogpu_classify_iab tool, so the model never touches your ZeroGPU keys, it just asks for a classification and gets the structured result back.
For the example, here is one real article, a product announcement, pasted in place of [article text]:
zerogpu_classify_iab and the classifier returns the signals it builds on:
🧩 Plug In Your Content Source and Output Destinations
The example above pastes one article into the chat and reads the outputs back. In a real workflow you’ll want to pull content from somewhere and push the results somewhere, and because everything runs through MCP, you can do both without writing code, just by adding more MCP servers to Claude Desktop alongside ZeroGPU.- Sending content in: Connect an MCP server for your content source (a CMS, a Google Drive, an RSS or web-fetch server) and ask Claude to grab the latest article, then run it through the same strategist steps. The IAB classifier sees whatever text Claude hands it.
- Sending outputs out: Connect MCP servers for your destinations (an email tool, an ads platform, a docs or CMS server) and tell Claude where each section goes, for example “send the Ad Brief to the campaign draft, the Newsletter Blurb to the email block, and the Content Pitch to a new doc.”
🚀 Go Deeper
This pipeline is a foundation. A few directions to extend it:- Content monetisation: Attach the returned IAB categories to each article as ad-targeting metadata, then use the confidence scores to pick the highest-value inventory automatically. Pages that classify cleanly into premium categories (for example Consumer Electronics at high confidence) can be routed to higher-CPM ad slots, while low-confidence pages fall back to broad inventory.
- Personalization pipelines: Run every incoming article through the classifier, then store the
audiencesegments per piece. When a reader arrives, match their on-site behavior to those segments and let Claude rewrite the same blurb in the voice that segment responds to, turning one article into many audience-specific variants. - Audience segmentation workflows: Batch-classify your whole content library and cluster pieces by their
iab_2_2categories and audience segments. The clusters become ready-made segments for email lists, ad campaigns, and editorial calendars, and Claude can draft a tailored pitch for each cluster from its dominant signals.
🌟 Highlights
This guide has walked you through combining ZeroGPU’s IAB classifier with Claude inside Claude Desktop to turn one article into three targeted outputs driven by real classification signals, with no code to write or run. You can adapt and expand this example for various other scenarios requiring classification signals to steer content generation. Key tools utilized in this guide include:- ZeroGPU IAB Classifier (
zlm-v1-iab-classify-edge): An edge-served model that maps any text straight to the IAB Content Taxonomy, returning content categories, audience segments, and a per-label confidence score in a single call. No instructions or prompt engineering needed, you send text and get structured signals back. See the model card. - ZeroGPU MCP Server: The hosted Model Context Protocol server at
https://mcp.zerogpu.ai/mcpthat exposes ZeroGPU’s edge models, including the IAB classifier aszerogpu_classify_iab, as MCP tools any client can call. Connect it once and Claude Desktop can reach the classifier directly. See the MCP server guide. - ZeroGPU: An ultra-fast, compute-efficient inference provider for apps and agents. We run purpose-built small and nano language models across an edge-powered network for the high-volume, purpose-specific tasks your app or agent runs constantly. Plug in our OpenAI-compatible API and you’re live - zero GPU infrastructure, serverless, auto-scaling by default.
- Claude Desktop: Anthropic’s desktop app for Claude. Here it orchestrates the pipeline: it connects to the ZeroGPU MCP server, calls the classifier as a tool, reads the returned IAB categories, audience segments, and confidence scores, and writes three distinct outputs grounded in those numbers.

