Cursor MCP guide

Test webhooks inside Cursor.

Add a project MCP configuration so Cursor can create temporary endpoints and inspect real deliveries while you work on the sender or receiver code.

Create → send → verify

Start with a sample webhook

Connect your assistant, send a sample event, and inspect what arrived. Free. No account or API key.

1. Connect your assistant

Merge into .cursor/mcp.json

{
  "mcpServers": {
    "webhooktest": {
      "url": "https://webhooktest.net/mcp"
    }
  }
}

Add this entry alongside any existing servers, then enable webhooktest in Cursor MCP settings. Reload if the tools do not appear.

Check that your assistant can discover the WebhookTest tools before continuing. Copying the configuration does not verify a connection.

2. Ask your assistant to run the test

Starter prompt

Use WebhookTest to create a temporary bucket named "My first AI webhook test". Show me its webhook_endpoint and dashboard_url, and keep the returned bucket ID for the next steps.

If you can execute HTTP requests, POST this JSON to that exact webhook_endpoint with Content-Type: application/json:
{"event":"hello.webhook","message":"My first AI webhook test"}

Otherwise, give me a copyable command for my operating system to send it, and pause until I confirm. WebhookTest's MCP tools inspect requests; they do not send the POST for you.

After sending, use wait_for_webhook or list_webhooks followed by get_webhook to retrieve the actual captured request. Verify that its method is POST and both JSON fields match. Show the captured values and dashboard link. Only report "Test passed" if the capture matches; a successful send or received:false is not proof. If nothing arrived, help me check the endpoint and send again.

No terminal access in your assistant? The prompt asks it for a command you can run yourself, then waits for your confirmation.

3. Verify the captured request

Example result — your assistant should produce this only after inspecting a matching capture.

✓ Endpoint created
✓ Webhook captured
✓ Method: POST
✓ event: hello.webhook
✓ message: My first AI webhook test

Test passed — the captured payload matches what was sent.

Next: point your own integration at the endpoint and ask your assistant to compare its payload with what you expected.

Setup and test workflow

01

Create the project configuration

Merge the quick-start JSON into .cursor/mcp.json, or enter the URL in Cursor MCP settings. The server is hosted, so no command, environment variable, or package install is required.

02

Reload MCP tools

Reload the window or toggle the server if Cursor does not discover tools immediately. Confirm the server reports eight tools before testing.

03

Keep the capability out of source

Let the agent use the returned bucket ID during the task, but do not commit bucket URLs to fixtures or documentation. Create a fresh bucket for each isolated scenario.

04

Debug from evidence

Trigger the integration and ask Cursor to compare the capture with the implementation. Use the dashboard link when a human-readable payload view is more convenient.

What the server exposes

Create and understand

`create_webhook_bucket` creates a temporary endpoint; `get_webhook_bucket` reads its name and response settings.

Observe deliveries

`wait_for_webhook` waits up to 25 seconds; `list_webhooks` paginates summaries; `get_webhook` returns one scoped capture.

Control and clean up

`configure_webhook_response` changes the reply. `clear_webhooks` and `delete_webhook_bucket` require explicit confirmation.

Privacy and limits

Retention policy update — effective October 8, 2026 at 22:00 UTC. Individual requests older than 15 days will be deleted, even in active buckets, including requests already stored. The existing 15-day bucket inactivity rule and per-bucket ceilings of 10,000 requests or 50 MiB remain unchanged. Cleanup is periodic, not deletion at an exact second. Retention details

Authorization, cookie, API-key, token, secret, password, and signature-like header or query values are redacted by default. Agents must explicitly request sensitive values. Bodies are limited to 64 KiB in tool output by default and can be raised only to 256 KiB. Use synthetic data: the endpoint is a debugging service, not a production processor.

Troubleshooting

  • Use the exact HTTPS URL and select remote or Streamable HTTP transport.
  • Restart or reload the client after changing MCP configuration.
  • Check that corporate policy allows the endpoint and outbound HTTPS.
  • A timeout with received:false is successful; verify the sender used the returned bucket URL.
  • HTTP 429 means the per-IP call, creation, bucket, or concurrent-wait limit was reached.

Client guides

MCP workflowClaudeCursorCodex