Use cases
A search tool for AI agents.
Agents search far more than people do. They need results they can read in one pass, at a price that doesn't make every lookup a budget decision.
How it works
- 1Hand the model a tool
Use the tool definition from the docs, or connect the MCP server and write no code at all.
- 2Run the search when it asks
One GET request returns titles, links and snippets as JSON.
- 3Let it choose what to read
The model picks the promising links and fetches those pages with its own tools.
Connect an agent with MCP
claude mcp add --transport http plainserp https://plainserp.com/mcp \
--header "Authorization: Bearer $PLAINSERP_KEY"Why it fits
- Results are plain JSON with no boxes to strip out, so tool results stay short.
- An MCP server and a skill file are ready to use.
- Failed searches cost nothing, so retries are free.
Know before you start
- It returns links and snippets. Your agent still needs a way to open pages.
- There are no AI Overviews or answer boxes. The model writes its own answer.
What it costs
An agent that makes 2,000 searches a day
That is 2,000 searches a day at $0.30 per 1,000. Your first 1,000 are free.
$0.60
a day