Market Research with Roo Code: Search, Trends, and Analysis

Market research is one of those tasks that sits outside the typical “coding agent” bucket but comes up constantly during product work. Competitor analysis before a sprint, landscape research before writing a pitch, keyword research before publishing content. The usual workflow is hopping between Google News, Trends, and regular search, running queries in each, and manually stitching together what you find.

Roo Code is an open-source AI coding agent that runs as a VS Code extension. It supports MCP tools, which means it can call multiple external services in a single session. Connect it to search, news, and trends tools and Roo Code can run the full research pipeline: query multiple sources, compare results, and synthesize a structured output.

This is the kind of multi-step task agents handle well. You describe the research goal, the agent queries the right sources in sequence, and you get back a structured brief rather than a pile of browser tabs.

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.

Example: Competitive Landscape Before a Sprint

You’re about to start work on a new feature and want competitive context. You ask Roo Code:

“Before we start, I want to understand the competitive landscape. Pull recent news on Vercel, Netlify, and Render. Check Google Trends to see which has the most search momentum over the last 6 months. Then search for any recent product announcements from each.”

Roo Code works through each step: calls Google News through AgentPatch for each platform, queries Google Trends for a comparison, and runs targeted Google searches for recent product updates. It returns a structured brief organized by company.

You then follow up:

“Based on what you found, what are the main themes in how these platforms are differentiating?”

Roo Code synthesizes across the data it just collected and gives you a thematic analysis. That’s strategic context before you write a line of code.

Example: Content Planning Research

Before writing a series of blog posts:

“I’m planning content for next month. Check Google Trends for these topics: ‘edge functions’, ‘server components’, ‘AI code review’, ‘monorepo tools’. Which are growing, which are flat? Then pull the top 3 recent articles on the growing ones.”

Roo Code runs the trend queries, identifies which topics have momentum, and follows up with targeted news searches on the winners. You get a content plan backed by data, not guesswork.

What Roo Code Does Step by Step

  1. Takes your research goal and breaks it into queries for each data source.
  2. Calls Google News, Google Trends, and Google Search through AgentPatch as needed.
  3. Collects all results and organizes them by the structure you requested.
  4. Synthesizes patterns across the data and presents a coherent brief.

The whole session takes a few minutes and produces research that would take much longer to do by hand. Because Roo Code keeps the conversation context, you can drill into any part of the results with follow-up questions.

Wrapping Up

A single AgentPatch connection gives Roo Code access to news, trends, web search, and the full tool marketplace. One MCP config entry covers all of it. Get started at agentpatch.ai.

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