# Building a Data Analyst Agent with Google ADK.

> Source: <https://dev.to/bwandere/building-a-data-analyst-agent-with-google-adk-5349>
> Published: 2026-09-21 08:50:39+00:00

At the recent Build with Google AI event in Kisumu, the core focus centered around a fundamental shift: moving from single-prompt chat completion to **Agentic Workflows**.

Instead of asking one LLM to solve a complex problem in a single turn, agentic patterns split tasks across specialized, autonomous units coordinated by an orchestrator.

To explore this hands-on, I built a Data Analyst Agent using the **Google Agent Development Kit (ADK)**. Here's a quick look at the build, the bugs I bumped into, and the concepts behind them.

Google's Agent Development Kit (ADK) is an open-source, code-first Python framework for building and testing AI agents. It gives you:

`adk web`) to monitor API calls, inspect payloads, and debug agent reasoning in real time.
A key concept when building agentic systems is the **Model Context Protocol (MCP)**. MCP serves as a standardized bridge between AI models and external data sources or execution environments.

Rather than hardcoding custom integrations for every database or API, MCP gives agents a uniform interface to securely read context, access files, and call tools across different systems.

I instantiated the agent in `agent.py` using standard ADK imports:

``` python
from google.adk import Agent

data_agent = Agent(
    name="data_analyst",
    model="gemini-2.5-flash",
    instruction="You are an expert Data Analyst AI...",
)
```

During local testing in the ADK web UI, I hit two quick configuration bumps:

`404 NOT_FOUND`)
`gemini-1.5-flash`), causing the platform to reject the request.` gemini-2.5-flash`.` 400 INVALID_ARGUMENT`)
`"gemini-2.5 flash"` instead of a hyphen), breaking the API URL parser.`.env` and `agent.py`.
After fixing the config files, I refreshed my local session using `gcloud auth application-default login`. Re-running `adk web` gave a clean `200 OK` status, allowing the agent to successfully process data requests and generate summaries.