Document Secure MCP Tunnel setup and deployment boundaries

[yia-mw-agent]

Parent

• PRD: Dedicated FAVA Data Repo MCP Tunnel for ChatGPT #67

What to build

Document how operators connect a private FAVA Trails data repo to ChatGPT using OpenAI Secure MCP Tunnel and the dedicated gateway runtime. The documentation should make the intended shape unambiguous: one long-lived gateway per data repo, tunnel-client runs inside the operator environment, and ChatGPT connects through the OpenAI-hosted tunnel without requiring a public FAVA endpoint.

The docs should also state the v1 boundaries so future agents do not expand the design back into per-agent aggregation, per-machine registries, Tailscale Aperture proxying, Cloudflare Tunnel as the mainline path, public HTTPS hosting, or MachineWisdom-specific deployment runbooks.

Acceptance criteria

• Operator docs explain required environment/configuration for the dedicated gateway runtime, including FAVA_TRAILS_DATA_REPO, Trust Gate provider config, and optional scope hinting.
• Docs include repeatable OpenAI Secure MCP Tunnel validation steps using tunnel-client init, tunnel-client doctor, and tunnel-client run.
• Docs describe ChatGPT connector setup and expected discovery behavior, including using list_scopes and explicit trail_name.
• Docs explain that the gateway is data-repo-owned and long-lived, not agent-owned and not tied to a product working directory.
• Docs warn that private FAVA data should not be exposed through a public endpoint without separately designed authentication, authorization, and hosting controls.
• Docs explicitly mark per-agent aggregation, per-machine registries, Tailscale Aperture integration, Cloudflare Tunnel mainline support, WiseMachine host assumptions, and public HTTPS hosting as out of scope for this v1 path.

Blocked by

• Add a dedicated ChatGPT gateway runtime #64
• Expose and verify the gateway-safe MCP workflow #65