The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Pipehero listing page.
Pipehero tunnels your localhost to a public URL and captures
every webhook, so you can inspect, replay, and debug them — including from your AI
agent via MCP.
This repo is auto-published from Pipehero's source. It holds the public MCP manifest and the agent skill. Issues/PRs welcome.
Let an agent (Claude Code, Cursor, Copilot, Windsurf, Zed, …) list your tunnels, read captured webhooks, and replay them to localhost.
Your client opens the browser to sign in and approve — no token to paste.
For CI/headless, pass a token from https://pipehero.app/dashboard/settings:
Any MCP client works — add it to .cursor/mcp.json, claude_desktop_config.json, etc.:
| Tool | What it does |
|---|---|
list_tunnels | Your tunnels and whether each is online. |
list_requests(subdomain) | Recent captured webhooks for a tunnel. |
get_request(subdomain, id) | Full request + response (headers + body). |
replay_request(subdomain, id) | Replay a webhook to your localhost. |
start_tunnel(name, port) | Expose a local port on a public URL (local MCP only). |
stop_tunnel(name) | Stop a tunnel started with start_tunnel (local MCP only). |
Because your agent has both the captured webhook and your codebase, it can explain why a handler failed — then fix it and replay to confirm.
Install the skill so your agent knows when and how to use Pipehero:
or copy SKILL.md into ~/.claude/skills/pipehero/SKILL.md.
MIT