HookWatch

For teams building AI agents, HookWatch’s MCP Proxy provides deep observability into tool calls. Every request and response is logged with full details, while latency metrics are computed for p50, p95, and p99 percentiles. When a tool times out or an agent loop stalls, error alerts fire instantly, often before users notice a degradation. The proxy integrates with zero code changes—simply point the MCP client at HookWatch’s endpoint—and optionally adds rate limiting and caching to protect back‑end services. Anomaly detection flags unexpected spikes in latency or error rates, so problems can be preempted. This visibility turns opaque LLM‑tool interactions into monitored, traceable workflows, enabling AI engineers to diagnose issues quickly.

HookWatch operates by acting as a transparent receiver for all incoming webhooks, cron pings, and MCP calls. Users create monitored endpoints within the dashboard or via the CLI, obtain a unique URL, and then point their providers—Stripe, GitHub, Shopify, or custom services—at that URL. Incoming requests are buffered, parsed, and forwarded to the user’s origin server; if the origin is down, HookWatch queues the events and retries automatically. For cron jobs, the CLI or cloud scheduler executes tasks and reports results back to the central monitor. All data flows into a unified, real‑time dashboard that shows event streams, success rates, and failure trends. Alerts are routed through integrations like Slack, Discord, PagerDuty, and email, ensuring developers receive immediate, actionable notifications wherever they work.

Consider a Stripe payment webhook that returns a 502 Bad Gateway at 3:02 AM. With HookWatch, the platform detects the failure, queues the event, and begins retrying with exponential backoff. At the same time, a Slack alert with full request details pings the on‑call engineer, who can inspect the payload and logs before the second retry. By the time the engineer checks, the automatic retry may have already succeeded, or the engineer can replay the event manually. In another scenario, a GitHub deploy hook is silently dropped by a misconfigured CI server. HookWatch logs every delivery attempt, making the gap immediately visible, and provides a replay option to trigger the pipeline. For AI‑driven workflows, long‑running MCP tool calls that time out are captured with trace‑level detail, so developers can optimize agent loops before they impact users.

HookWatch is built for developers, SREs, and platform engineers who need reliable webhook infrastructure without the overhead of enterprise monitoring suites. It supports modern stacks running on any platform—no custom integration required to connect with services like Vercel, Twilio, Linear, or Paddle. Pricing starts with a generous free tier that covers 10 endpoints, 5 cron jobs, and 7‑day history, then scales to paid plans for larger teams and unlimited endpoints. The local‑first CLI provides full offline capability, while the cloud dashboard and alerting tie everything together. In a world where 58% of webhook failures occur outside business hours, HookWatch ensures that developers learn about problems in seconds, not hours, keeping revenue, data, and user experience intact. It’s the all‑in‑one observability layer for the invisible plumbing of modern applications.