Agno market research

Combine category facts, launches, and live price signals.

What you’ll build

An Agno agent that assesses the US market for home espresso grinders under USD 800. It separates durable category and manufacturer facts from recent launches and time-sensitive marketplace signals, then writes a decision-ready market report.

Default brief: Map the category, representative products, gaps, and risks. Treat live price and availability as signals—not permanent product facts—and include source URLs.

How the agent works

  1. Frame the category. Web search establishes segments, manufacturers, and durable product facts.
  2. Check current signals. News finds launches while shopping search captures live prices and availability.
  3. Reconcile the market. The agent compares the evidence, calls out gaps, and stays within a ten-call tool budget.

Core agent setup

This abridged excerpt keeps the Agno agent and tool boundary in view. The full script also handles model configuration, environment validation, and Markdown output.

agent = Agent(
    name="SerpApi market researcher",
    model=model,
    instructions=[
        "Search before making market claims.",
        "Use the most specific SerpApi tool for each question.",
        "Separate live listing signals from durable category facts.",
    ],
    tools=[
        web_search(provider="agno", allowed_engines=["google_light", "bing"]),
        news_search(provider="agno"),
        shopping_search(provider="agno"),
    ],
    markdown=True,
    tool_call_limit=10,
)
response = agent.run(PROMPT)

View the complete main.py →

Run the recipe

Set SERPAPI_API_KEY and XAI_API_KEY in the repository-root .env, then run:

uv run --isolated --no-project --with 'serpapi-search-tools[agno]' --with python-dotenv cookbook/agno/main.py

Optional controls: XAI_MODEL, XAI_BASE_URL, COOKBOOK_PROMPT, and COOKBOOK_OUTPUT_DIR.

Portable environment: --isolated --no-project runs the local recipe against the published serpapi-search-tools[agno] package instead of importing this checkout.

Inspect the result

The recipe writes cookbook-output/agno-market-research.md. Expect category segments, representative products, current price signals, market gaps, risks, and direct source URLs.

The same report is printed to the terminal. Set COOKBOOK_OUTPUT_DIR to move the saved artifact, or COOKBOOK_PROMPT to research another category.

SerpApi tools used

web_search supplies category and manufacturer facts, news_search tracks recent launches, and shopping_search captures current prices and availability. Keeping these result types separate helps the agent label which signals are durable and which may change quickly.

Framework pattern: The agent structure is inspired by Agno’s parallel market research cookbook; this recipe applies it to three SerpApi evidence surfaces.