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## The Future Is Already Here (And It's Weird)
Three months in, here's what's blowing my mind:
We're not getting better AI. We're getting AI teams. And honestly? They're better coworkers than some humans I've worked with.
**What's happening in my team right now**:
- New hire learned our codebase in 2 days using our agents
- Our deployment agent caught a config issue that would've taken down prod
- Junior dev using our senior-dev-trained agents is shipping senior-level code
- I haven't manually written a test in weeks (and our coverage is up 40%)
**My prediction**: In 6 months, "Do you have good agents?" will be as important as "Do you have good docs?" when joining a team.
## Just Try It. Seriously.
Stop reading. Start doing. 15 minutes:
**1. Install** (copy-paste this):
```bash
npm install -g @anthropic/claude-code
```
**2. Create an agent** (steal mine):
```bash
mkdir -p .claude/agents
# Copy any agent from this post
# Start with the code reviewer - it's the gateway drug
```
**3. Use it on your actual code**:
```bash
claude "Review my latest changes"
# When it finds that bug you missed, you'll get it
```
**4. Thank me later**:
- Tweet me what your agent caught
- Share your agents on GitHub
- Help someone else level up
**Last week's scoreboard**:
- Race condition caught: 1
- Tests written: 247
- Hours saved: ~15
- Times I've said "holy shit" out loud: 6
**This week**: Teaching my agents our new microservices patterns. They learn faster than I do.
Look, I was skeptical too. "Another AI tool" I thought. But this isn't just a tool. It's like hiring a team of experts who work 24/7, never complain, and get better every day.
Your move. Build your team or watch others build theirs.
<|endoftext|>
# source: VoltAgent__voltagent/website/blog/2025-04-26-peaka-mcp-voltagent/index.md type: docs
---
title: Building a Data-Aware Chatbot with VoltAgent and Peaka
description: Learn how to integrate Peaka's powerful data access into your VoltAgent AI applications using the Model Context Protocol (MCP).
slug: data-aware-chatbot-voltagent-peaka
tags: [mcp, tutorial]
image: https://cdn.voltagent.dev/2025-04-26-peaka-mcp-voltagent/social.png
authors: omeraplak
---
import GitHubExampleLink from '@site/src/components/blog-widgets/GitHubExampleLink';
## Introduction
In this article, I'll demonstrate how we can use the Model Context Protocol (MCP) by integrating **VoltAgent** and **Peaka** to create an AI agent with data retrieval capabilities.
![Peaka MCP VoltAgent](https://cdn.voltagent.dev/2025-04-26-peaka-mcp-voltagent/peaka-demo.gif)
<GitHubExampleLink
repoUrl="https://github.com/VoltAgent/voltagent/tree/main/examples/with-peaka-mcp"
npmCommand="npm create voltagent-app@latest -- --example with-peaka-mcp"
/>
## Wait, What's Peaka?
Right, before I show you the code stuff, let me tell you about [Peaka](https://www.peaka.com/).
Their idea is pretty simple: make it less annoying to work with data. Think of it like a data middleman. You hook up your databases, spreadsheets, whatever, to Peaka. Then you can ask it questions (using fancy SQL code or just regular English), and it pulls the info together from all those places for you.
Usually, connecting different data sources is a real pain and costs a lot. Peaka feels like a simpler option, especially if you're not a huge company or just don't want to mess with complicated data pipelines. They wanna be the easy button for getting data.
## And VoltAgent?
It's our toolkit for putting together AI powered applications. We provide the core engine (`@voltagent/core`) to get you started, and then you can add extra capabilities, like voice interaction (`@voltagent/voice`) or support for different LLMs (OpenAI, Google, etc.). VoltAgent handles the complex stuff (like history a...
We designed VoltAgent to hit a nice sweet spot. It gives you more helpful structure than trying to build everything from raw AI libraries, but it offers a lot more freedom and customization than the simpler no-code platforms out there.
:::tip
We also built the [VoltOps LLM Observability Platform](https://console.voltagent.dev) a web interface that lets you monitor your agents, see exactly how they're working, and chat with them directly. We find it incredibly useful ourselves for debugging and testing!