I gave my Cursor agent real tools without five API keys

Last week, I wanted to build an AI agent that could do more than chat.

My goal was simple:

Surprisingly, the LLM wasn't the bottleneck.

The real challenge was the setup.

Every capability required another tool:

For a one-off experiment, I spent more time connecting tools than actually building the workflow.

So I tried using Vaaya as a single MCP server inside Cursor.

Install Vaaya MCP:

npx @vaaya/mcp install

It automatically added this to my Cursor MCP configuration:

{
  "mcpServers": {
    "vaaya": {
      "command": "npx",
      "args": ["-y", "@vaaya/mcp"]
    }
  }
}

Then I simply:

vaaya

was runningThat was the entire onboarding experience.

Using Vaaya tools:

1. Open our product in a live browser and record a short walkthrough.
2. Find 15 Series A SaaS Product Managers matching our ICP.
3. Enrich their work email addresses.
4. Draft short outreach in our brand tone.

Show every step while you work.

Do not send anything.
Drafts only.

I intentionally kept everything in draft mode so I could review the output before anything was sent.

✅ One MCP instead of managing multiple vendor accounts for a demo

✅ Tool calls were visible inside the agent UI, making it easier to understand and debug what the agent was doing

✅ Pay-per-successful-call felt much better for experimentation than paying for multiple monthly subscriptions

If you're a:

…and you're spending more time wiring APIs than testing ideas, this approach is worth trying.

It's not magic.

It just removes a lot of the setup friction between:

"I have an idea."

and

"My agent actually called the tools."

You can check it out here:

https://vaaya.ai/

https://www.linkedin.com/company/vaayaio/posts/

https://x.com/getvaaya

If you've built similar agent workflows, I'd love to know what your stack looks like.

What part of the setup still feels the most painful?

#AI

#MCP

#Cursor

#AIAgents

#AgenticAI

#DeveloperTools

#Productivity

#Automation

#LLM

#DevTools