How to Build a Universal AI Toolkit: A Guide to Mastering Agentic AI in VS Code

So, you're all in on agentic AI. You're running powerful assistants in VS Code, but you've hit the inevitable wall: how do you give your agents the tools they need to be truly effective? You have a local stdio server for file access, an sse server streaming logs, and a standard HTTP server for a RAG pipeline. The question is, what's the best way to configure MCP servers like these?

If you're tired of the manual setup and security risks, this guide is for you. We'll walk through the definitive method to create a universal AI toolkit that works for any agent, in any project.

The Manual Mess: Why Your Current Setup Isn't Working

When developers first start, they learn how to add tools to AI agents by editing settings files directly. This works for one tool and one agent, but it quickly falls apart. You might have a local tool and need to connect your agent to a local server, but then you add a cloud tool, and the process is different.

This manual approach violates several agentic AI security best practices. Pasting raw API keys into multiple JSON files is not a secure or scalable solution.

You need a better architecture. You need a tool proxy.

The Professional Solution: Build a Tool Proxy for Your AI Agents

Instead of connecting each agent to each tool, the correct approach is to build a central proxy. This proxy acts as a single, secure gateway. Your agents connect to the proxy, and the proxy securely manages the connections to all your underlying tools.

This architecture offers two massive advantages:

1. Centralized Management: You configure all your tools—http, stdio, and sse—in one place.
2. Airtight Security: Your agents only need one key to access the proxy. They never see the sensitive credentials for your actual tools.

But building a proxy from scratch is a lot of work. That's where OrbitalMCP comes in.

How to Create a Universal AI Toolkit with OrbitalMCP

OrbitalMCP is a ready-made, secure tool proxy. Here's how you can use it to master your agentic workflow in minutes.

Step 1: Unify Your Tools in the OrbitalMCP Dashboard

First, you add all your different MCP servers to your secure OrbitalMCP dashboard. Our platform is designed to handle every type, so you have a clear guide to sse MCP servers and know exactly how to use stdio MCP server configurations right alongside your standard HTTP tools. This becomes your single source of truth.

Step 2: Use the Universal OpenAPI Endpoint

Once your tools are configured, OrbitalMCP provides you with a single, unique URL. This URL leads to a dynamically generated OpenAPI for AI agent tools. This isn't just a generic file; it's a personalized "instruction manual" for your agents that describes every single tool you've configured.

Step 3: Connect Any Agent in Seconds

Now for the easy part. You open the tool configuration for any agent in your IDE—Claude, Copilot, Gemini, etc.—and instead of manually adding each tool, you provide your one single OrbitalMCP OpenAPI URL.

The agent instantly connects, reads the personalized manual, and discovers your entire toolkit. The process is identical for every agent, making it the definitive solution for mastering agentic AI in VS Code.

The Future is Centralized

Stop wrestling with individual configurations and security vulnerabilities. By using a centralized tool proxy like OrbitalMCP, you can finally move past the setup phase and unlock the true power of your AI assistants. Your workflow becomes more secure, more manageable, and infinitely more powerful.

Ready to build your universal AI toolkit? Sign up for a free OrbitalMCP account at www.orbitalmcp.com and transform your agentic AI workflow today.