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Gemini Search

Gemini Search

Section titled “Gemini Search”

OpenClaw supports Gemini models with built-in Google Search grounding, which returns AI-synthesized answers backed by live Google Search results with citations.

Get an API key

Section titled “Get an API key”

  1. Create a key

    Go to Google AI Studio and create an API key.

  2. Store the key

    Set GEMINI_API_KEY in the Gateway environment, or configure via:

    Terminal window
    openclaw configure --section web

Config

Section titled “Config”
{
  plugins: {
    entries: {
      google: {
        config: {
          webSearch: {
            apiKey: "AIza...", // optional if GEMINI_API_KEY is set
            model: "gemini-2.5-flash", // default
          },
        },
      },
    },
  },
  tools: {
    web: {
      search: {
        provider: "gemini",
      },
    },
  },
}

Environment alternative: set GEMINI_API_KEY in the Gateway environment. For a gateway install, put it in ~/.openclaw/.env.

How it works

Section titled “How it works”

Unlike traditional search providers that return a list of links and snippets, Gemini uses Google Search grounding to produce AI-synthesized answers with inline citations. The results include both the synthesized answer and the source URLs.

  • Citation URLs from Gemini grounding are automatically resolved from Google redirect URLs to direct URLs.
  • Redirect resolution uses the SSRF guard path (HEAD + redirect checks + http/https validation) before returning the final citation URL.
  • Redirect resolution uses strict SSRF defaults, so redirects to private/internal targets are blocked.

Supported parameters

Section titled “Supported parameters”

Gemini search supports the standard query and count parameters. Provider-specific filters like country, language, freshness, and domain_filter are not supported.

Model selection

Section titled “Model selection”

The default model is gemini-2.5-flash (fast and cost-effective). Any Gemini model that supports grounding can be used via plugins.entries.google.config.webSearch.model.

Section titled “Related”