Webhook MCP Server

Overview

The Webhook MCP Server provides a lightweight, plug‑in style interface for sending instant notifications from AI assistants to any webhook‑capable service. When an assistant completes a long‑running task—such as data aggregation, model inference, or workflow orchestration—it can trigger this server to POST a payload to a user‑specified endpoint. This pattern is especially useful for integrating AI workflows with external monitoring tools, chat platforms, or custom dashboards that rely on webhooks to surface status updates.

Developers using AI assistants often need to keep stakeholders informed without polluting the assistant’s conversational thread. By offloading notification logic to a dedicated MCP server, the assistant can remain focused on generating content while the server handles HTTP communication, authentication headers, and retry logic. The server exposes a single “notification” resource that accepts a JSON body containing the message, context metadata, and optional custom fields. This abstraction keeps the assistant’s prompts concise: a simple instruction like “notify me when this job finishes” is all that’s required.

Key capabilities of the Webhook MCP Server include:

• Dynamic endpoint configuration – The webhook URL is supplied via an environment variable (), allowing the same binary to be reused across projects or environments.
• Cross‑platform deployment – It can run natively through , be containerized with Docker, or be installed directly from Smithery for seamless integration into Claude Desktop, Cursor, or Windsurf.
• Lightweight footprint – The server performs a single HTTP POST and exits, minimizing resource usage for transient notification tasks.
• Extensibility – The MCP protocol permits additional tools or prompts to be added later, such as rate limiting or payload transformation, without changing the core notification logic.

Typical real‑world scenarios include:

• Long‑running batch jobs: A data pipeline triggers an AI model that may take minutes; the assistant notifies the user via Slack, Microsoft Teams, or a custom dashboard once results are ready.
• CI/CD pipelines: Build processes that invoke AI‑powered code reviews can send a webhook to a CI server, allowing automated deployment scripts to react when the review is complete.
• User experience enhancement: Chatbots that handle heavy computation can inform users through push notifications or in‑app messages, improving perceived responsiveness.

Integration into AI workflows is straightforward. After configuring the server with the desired webhook URL, a prompt can include a call to the “notification” resource. The assistant sends the request, the server forwards it, and the external service receives a ready‑to‑consume payload. This decoupling allows teams to mix and match notification services—such as Echobell, Zapier, or custom webhooks—without modifying the assistant’s core logic.