Building a Research Assistant with OpenClaw and Web Search

OpenClaw already handles conversation well. With web search added, it can also gather and synthesize information on demand — which is most of what a research assistant needs to do.

Why This Matters

A research assistant isn’t just a chatbot. It needs to pull current information, cross-reference sources, and summarize what it finds into something useful. That requires the ability to actually search the web, not just recall facts from training.

OpenClaw is a good foundation for this: it runs locally, works with chat interfaces you already use (Telegram, Discord, Signal), and supports MCP tools. Adding AgentPatch gives it Google Search, which is enough to handle most research tasks.

The key difference from just googling something yourself is that the agent can search, read results, and synthesize an answer in one step. You describe what you want to know, it figures out what to search for, and it gives you a summary — not a list of links.

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

You message your OpenClaw bot on Telegram:

“Can you give me a quick overview of how the EU AI Act affects companies deploying foundation models? Specifically the obligations around transparency.”

The bot runs a few targeted searches:

Searching Google for "EU AI Act foundation model providers obligations 2025"...
Searching Google for "EU AI Act GPAI transparency requirements"...

Here's what I found:

Under the EU AI Act, providers of General Purpose AI (GPAI) models — which includes
foundation models — have several transparency obligations:

1. They must publish a summary of training data, including sources and any copyrighted
   material used.
2. They must provide technical documentation sufficient for downstream deployers to
   understand capabilities and limitations.
3. High-capability GPAI models (above 10^25 FLOPs training compute) face additional
   requirements including adversarial testing and incident reporting.

The transparency rules took effect in August 2025. Non-compliance can result in fines
up to 3% of global annual turnover.

Want me to dig into any of these areas further?

The agent pulled current information, synthesized it, and offered to go deeper. That’s more useful than a link to the EUR-Lex page.

Wrapping Up

Web search turns OpenClaw from a conversational bot into something that can actively gather information for you. Connect AgentPatch once and you also get access to Bing Search, image search, and every other tool on the marketplace — no extra setup. More at agentpatch.ai.

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