Docs
Getting started with z-gateway.
Connect an AI agent through a governed MCP gateway, route GitHub or Postgres actions through policy checks, start in monitor mode, and review the first runtime sessions in the dashboard.
Setup path
- 01
Create your account
Sign up for z-gateway and use the hosted dashboard to configure your first workspace. - 02
Create a workspace
Workspaces isolate agents, policies, GitHub and Postgres connectors, runtime sessions, approvals, logs, and team access. - 03
Connect GitHub and/or Postgres
Install the GitHub App for repository workflows or add a hosted Postgres target for governed database tools. - 04
Register an agent
Create an agent identity in the dashboard. This identity is used in policy matching and audit logs. - 05
Get the MCP setup command
Open the agent MCP configuration panel and copy the command generated for your MCP client. - 06
Configure your MCP client
Use the one-command setup for Codex, Claude, or a generic MCP client. Do not paste real secrets into documentation or shared files. - 07
Test a safe action
Start with a read_repo call, schema read, or bounded read-only query to confirm routing and logging. - 08
Review runtime sessions
Confirm the action appears in a session timeline with the agent, connector, target resource, decision, and policy reason.
One-command MCP setup
The dashboard fills in the credential ID for your registered agent. The command shape is:
npx -y @z-gateway/cli mcp add \
--gateway https://z-gateway.com \
--credential-id <credential-id> \
--environment dev \
--client claude-codeFor the full client-specific setup flow, see MCP Setup.
Recommended rollout
Start in monitor mode so z-gateway evaluates and logs decisions without blocking. Review logs for expected actions, add or tighten policies, then move high-risk actions or production agents into enforce mode.