Building a Visual Content Pipeline with OpenClaw

If you produce visual content regularly — blog posts, newsletters, social updates — a significant portion of the time goes into finding relevant images or generating them. OpenClaw can automate that when connected to the right tools. With AgentPatch, the image generation and research steps both live in the same agent workflow.

Why This Matters

A visual content pipeline has a few consistent steps: understand the topic, decide on a visual direction, generate or source the image, and integrate it. OpenClaw can handle all of these when it has access to search and image generation tools.

Without AgentPatch, each of those steps requires a separate tool or manual process. With AgentPatch connected, OpenClaw can run the full pipeline in a single interaction — using Google Search for context, Google News for current angles, and Recraft for image generation.

Setup

The AgentPatch CLI is designed for AI agents to use via shell access. Install it, and your agent can discover and invoke any tool on the marketplace.

Install (zero dependencies, Python 3.10+):

pip install agentpatch

Set your API key:

export AGENTPATCH_API_KEY=your_api_key

Example commands your agent will use:

ap search "web search"
ap run google-search --input '{"query": "test"}'

Get your API key from the AgentPatch dashboard.

Install the AgentPatch skill from ClawHub — it teaches OpenClaw when to use AgentPatch and how to use the CLI:

clawhub install agentpatch

MCP Server (Alternative)

If you prefer raw MCP tool access instead of the skill, add AgentPatch to ~/.openclaw/openclaw.json:

{
  "mcp": {
    "servers": {
      "agentpatch": {
        "transport": "streamable-http",
        "url": "https://agentpatch.ai/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_KEY"
        }
      }
    }
  }
}

Replace YOUR_API_KEY with your actual key from the AgentPatch dashboard. Restart OpenClaw and it discovers all AgentPatch tools automatically.

Example

Here’s a practical visual content pipeline using OpenClaw. You send your bot:

“I’m writing about the rise of local AI models. Research what’s happening this week, identify the most visually interesting angle, and generate a header image that would work for a tech blog post. Dark background, modern illustration style.”

OpenClaw works through this step by step:

  1. Calls Google News through AgentPatch to find recent stories about local AI models
  2. Identifies a specific angle — say, consumer hardware enabling local inference
  3. Calls Recraft through AgentPatch to generate a header image matching that angle
  4. Returns the image along with a summary of the research

You get a header image grounded in current content, not a generic stock-photo guess. The whole thing runs in one message.

You can refine the pipeline further:

“Do the same for three different topics I’m covering this month, generate a header image for each, and give me a short description I can use as alt text.”

OpenClaw runs the research and image generation steps three times in sequence, returning all three images with alt text.

Wrapping Up

OpenClaw with AgentPatch handles the repetitive research-and-visual parts of a content workflow so you can focus on writing. The same connection that gives you image generation also covers search, news, email, and maps. See everything available at agentpatch.ai.

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