Every AI agent needs its own identity.

Connect your services once — Stripe, Vercel, Cloudflare, and more. Give every AI agent scoped access with read and write controls, log every credential request, and revoke anytime without rotating a single key.

You have IAM for your team. Not for your agents.

You wouldn't give a new hire unrestricted access to every system on day one. You give them only what they need — the principle of least privilege. You review sensitive actions. You know what they've accessed. And when they leave, you remove their access.

AI agents deserve the same controls. Gazebo brings credential management to every AI agent — scoped identities, read/write controls, and a complete audit trail so you can safely deploy agents across your production systems.

Without Gazebo

Agents inherit full access from shared API keys.
Every new agent gets the same permissions.
No read/write controls — agents can do anything the key allows.
If something goes wrong, you're left piecing together logs.
Revoking one agent often means rotating credentials for everyone.

With Gazebo

Every agent gets its own scoped identity.
Each agent only accesses the services and operations you allow.
Read/write controls per agent — define exactly which operations each one can perform.
Every credential request is logged with a complete audit trail.
Revoke an individual agent instantly without changing your API keys.

Contain the blast radius.

Gazebo is the credential broker between your agents and your APIs — each agent gets a scoped token, the real key stays in the vault. One agent reads Stripe. Another updates Cloudflare DNS. A third manages Vercel environment variables. Each is blocked from everything else. If one is compromised, its policy limits the damage — not your API key.

Revoke any agent. Instantly. Without touching your keys.

When an agent exceeds its scope or a project ends — revoke it in one click. The token is invalidated immediately. Your Stripe, Vercel, and Cloudflare credentials stay untouched. Every other agent keeps working. No key rotation required.

Know exactly what happened — and who did it.

Gazebo records which agent made the request, which service it accessed, which operation it attempted, and whether it was allowed or blocked. When something breaks, you don't hunt through logs. You already know.

No rewrites. Works with the agents you're already using.

Every agent identity gets its own bearer token for Gazebo's MCP endpoint. Drop it into Cursor, Claude Code, or any MCP-compatible client — the token carries the agent's permissions automatically. No custom integrations. No new permission systems to manage. No rewriting your tools.

Share agents the way OAuth made apps shareable.

Publish any agent with a declared scope. Anyone with the install link sees exactly what it needs before approving — and grants access from their own services, not yours. You never touch their credentials.

Declared scope is locked at publish — can't be quietly expanded
Installer's credentials are sovereign — the author has zero access
Every access is logged in the installer's own audit trail
One-click revocation, independent of the agent author

Frequently asked questions

What is IAM for AI agents?: IAM (identity and access management) for AI agents applies the same principles you already use for employees — scoped permissions, audit logs, and revocable access — to the AI tools and agents that call your APIs. Instead of handing an agent your full Stripe or GitHub key, Gazebo gives it a scoped identity that can only do what you've explicitly allowed.
How is Gazebo different from a secrets manager?: A secrets manager (like HashiCorp Vault, AWS Secrets Manager, or 1Password) stores your credentials securely. Gazebo sits on top of that: it's the access-control and audit layer that decides which AI agent can retrieve which credential, logs every retrieval, and lets you revoke one agent's access without rotating the underlying key.
What happens if an AI agent is compromised?: The damage is bounded by that agent's access profile, not by everything your API key can touch. If a Cursor agent only has scoped access to Stripe webhooks, a compromised agent can't reach your Vercel environment variables or Cloudflare DNS. You can also revoke its access instantly from the dashboard — no key rotation required.
Do I need to rotate my API keys to revoke an agent's access?: No. Gazebo issues each agent its own scoped token, separate from your underlying service credentials. Revoking an agent's access invalidates its token immediately — your actual Stripe, GitHub, or Vercel API key stays unchanged and every other agent keeps working.
Does Gazebo work with MCP-based agents like Cursor and Claude Code?: Yes. Every access profile exposes a standard MCP endpoint you can drop directly into Cursor, Claude Code, or any MCP-compatible client. The permissions you define follow the agent automatically — no extra configuration needed.
Can I give one agent read-only access while another has full write access?: Yes. Gazebo lets you define read/write controls per agent per service — you can allow one agent to GET Stripe data while blocking it from creating webhooks, and allow a separate agent to POST to Cloudflare DNS while keeping everything else off-limits. Permissions follow the HTTP method (GET, POST, PUT, DELETE), not just the service.

From the writing

API Credential Management: The Complete Guide — How to store, scope, rotate, audit, and revoke API keys and tokens across your systems — including the specific ways AI agents change the calculus. Covers the full credential lifecycle, four storage patterns, the rotation vs. revocation question, and how to choose between Vault, AWS Secrets Manager, Doppler, and Gazebo.
Windsurf AI Agent Credentials: How to Scope Cascade's API Access — Windsurf's Cascade agent inherits full-access credentials from your environment by default — the same keys that let it call an API also let it do everything else that key covers. A scoped MCP connection narrows access to the task and adds an audit trail without changing how Windsurf works.
Secret Scanning for AI Codebases: What It Catches and What It Misses — Secret scanning catches credentials that land in committed files and git history. AI agents add an exposure surface scanning was never designed to cover: credentials in prompts, conversation context, and tool-call logs. Here's how to close the gap.
Service Accounts vs. Agent Tokens: What's the Difference — Service accounts were built for predictable infrastructure automation. AI agents aren't predictable in the same way — and the mismatch creates real security problems when teams reach for service accounts out of habit.