AI agents need a safer way to use API keys

AI agents are quickly becoming part of real developer workflows.

They can deploy apps, update databases, trigger automations, manage payments, create issues, read docs, and interact with dozens of services. But there is one uncomfortable problem behind all of this:

Most agents still need access to API keys.

Today, that usually means copying raw credentials into .env files, MCP servers, automation tools, local projects, dashboards, or different AI coding environments.

That may work at the beginning, but it gets messy fast.

You start asking questions like:

• Where did I store that key?

• Which agent has access to it?

• Which project is using this account?

• What happens if I need to switch accounts?

• Do I need to generate another key?

• What if the provider only showed the key once?

• How do I revoke access without breaking everything?

This becomes even harder when you work with multiple accounts for the same service.

For example: multiple Supabase projects, Stripe accounts, Vercel teams, GitHub orgs, Cloudflare accounts, or client workspaces.

That is the problem we are working on with TuMCP.

The idea is simple:

Instead of giving your AI agent direct access to every raw API key, you connect your accounts once inside TuMCP and generate one MCP key for the agent.

Your agent only sees that bridge key.

Behind it, you control which real account or workspace is active. If you need to switch from one account to another, you can do it with one click without reconfiguring the MCP server or creating a new API key.

We believe API access for AI agents needs a control layer.

Not just a place to store secrets, but a way to decide what an agent can access, which account it should use, and when that access should change.

That is what we are building with TuMCP: a secure API key control layer for AI-powered development workflows.

Would love to hear from other builders:

How are you currently managing API keys across AI agents, MCP servers, and multiple accounts?