Setup Webhook logo

Setup Webhook

Organization
VapiAI
setup-webhook

Configure Vapi server URLs and webhooks to receive real-time call events, transcripts, tool calls, and end-of-call reports. Use when setting up webhook endpoints, building tool servers, or integrating Vapi events into your application.

Overview

PublisherVapiAI
Repositoryskills
Skill namesetup-webhook
Stars
68
Forks
8
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by VapiAI on GitHub. Read the source before you install it.

Installation

Install the Setup Webhook AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/VapiAI/skills/tree/main/plugins/vapi-voice-ai/skills/setup-webhook
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/VapiAI/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/vapi-voice-ai/skills/setup-webhook .claude/skills/setup-webhook
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Setup Webhook in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Setup Webhook on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Setup Webhook is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Vapi Webhook / Server URL Setup

Configure server URLs to receive real-time events from Vapi during calls — transcripts, tool calls, status changes, and end-of-call reports.

Setup: Ensure VAPI_API_KEY is set. See the setup-api-key skill if needed.

Overview

Vapi uses "Server URLs" (webhooks) to communicate with your application. Unlike traditional one-way webhooks, Vapi server URLs support bidirectional communication — your server can respond with data that affects the call.

Where to Set Server URLs

On an Assistant

bash
curl -X PATCH https://api.vapi.ai/assistant/{id} \
  -H "Authorization: Bearer $VAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "server": {
      "url": "https://your-server.com/vapi/webhook",
      "credentialId": "cred_abc123"
    }
  }'

Create the optional credentialId in Dashboard > Custom Credentials. Omit it only for a deliberately public endpoint.

On a Phone Number

Phone-number updates also use a server object with url and optional credentialId. When updating through the API, first retrieve the number and preserve its existing provider discriminator in the PATCH body. The dashboard is the safest choice when the provider is unknown.

At the Organization Level

Set a default server URL in the Vapi Dashboard under Settings > Server URL.

Priority order: Tool server URL > Assistant server URL > Phone Number server URL > Organization server URL.

Event Types

EventDescriptionExpects Response?
assistant-requestRequest for dynamic assistant configYes — return assistant config
tool-callsAssistant is calling a toolYes — return tool results
status-updateCall status changedNo
transcriptReal-time transcript updateNo
end-of-call-reportCall completed with summaryNo
hangAssistant failed to respondNo
speech-updateSpeech activity detectedNo

Webhook Server Example (Express.js)

typescript
import express from "express";
const app = express();
app.use(express.json());

app.post("/vapi/webhook", (req, res) => {
  const { message } = req.body;

  switch (message.type) {
    case "assistant-request":
      // Dynamically configure the assistant based on the caller
      res.json({
        assistant: {
          name: "Dynamic Assistant",
          firstMessage: `Hello ${message.call.customer?.name || "there"}!`,
          model: {
            provider: "openai",
            model: "gpt-4.1",
            messages: [
              { role: "system", content: "You are a helpful assistant." },
            ],
          },
          voice: { provider: "vapi", voiceId: "Elliot", version: 2 },
          transcriber: { provider: "deepgram", model: "nova-3", language: "en" },
        },
      });
      break;

    case "tool-calls":
      // Handle tool calls from the assistant
      const results = (message.toolCallList || []).map((toolCall: any) => ({
        toolCallId: toolCall.id,
        result: handleToolCall(
          toolCall.name,
          toolCall.parameters || toolCall.arguments
        ),
      }));
      res.json({ results });
      break;

    case "end-of-call-report":
      // Process the call report
      console.log("Call ended:", {
        callId: message.call.id,
        endedReason: message.endedReason,
        cost: message.cost,
        analysis: message.analysis,
        artifact: message.artifact,
      });
      res.json({});
      break;

    case "status-update":
      console.log("Call status:", message.status);
      res.json({});
      break;

    case "transcript":
      console.log(`[${message.role}]: ${message.transcript}`);
      res.json({});
      break;

    default:
      res.json({});
  }
});

function handleToolCall(name: string, args: any): string {
  // Implement your tool logic here
  return `Result for ${name}`;
}

app.listen(3000, () => console.log("Webhook server running on port 3000"));

Webhook Server Example (Python / Flask)

python
from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route("/vapi/webhook", methods=["POST"])
def vapi_webhook():
    data = request.json
    message = data.get("message", {})
    msg_type = message.get("type")

    if msg_type == "assistant-request":
        return jsonify({
            "assistant": {
                "name": "Dynamic Assistant",
                "firstMessage": "Hello! How can I help?",
                "model": {
                    "provider": "openai",
                    "model": "gpt-4.1",
                    "messages": [
                        {"role": "system", "content": "You are a helpful assistant."}
                    ],
                },
                "voice": {"provider": "vapi", "voiceId": "Elliot", "version": 2},
                "transcriber": {"provider": "deepgram", "model": "nova-3", "language": "en"},
            }
        })

    elif msg_type == "tool-calls":
        results = []
        for tool_call in message.get("toolCallList", []):
            results.append({
                "toolCallId": tool_call["id"],
                "result": f"Handled {tool_call['name']}",
            })
        return jsonify({"results": results})

    elif msg_type == "end-of-call-report":
        print(f"Call ended: {message['call']['id']}")
        print(f"Summary: {message.get('analysis', {}).get('summary')}")

    return jsonify({})

if __name__ == "__main__":
    app.run(port=3000)

Webhook Authentication

Use a Vapi Custom Credential and place its ID in server.credentialId. Vapi supports Bearer Token, OAuth 2.0 client credentials, and HMAC credentials. Verify requests according to the credential you configured; HMAC header names, algorithms, timestamps, and payload formats are configurable, so do not assume a fixed x-vapi-signature format.

For a bearer credential, compare the incoming Authorization: Bearer <token> value with the token stored securely by your server. Never put the secret itself in an assistant or phone-number payload.

Local Development

Use the Vapi CLI with a public tunnel. The CLI forwards from port 4242 to your app, but it does not create the public URL itself:

bash
# Install the CLI
curl -sSL https://vapi.ai/install.sh | bash

# Terminal 1: expose the CLI listener
ngrok http 4242

# Terminal 2: forward events from the CLI to your app
vapi listen --forward-to localhost:3000/vapi/webhook

Set the Vapi server URL to the public ngrok URL. To skip the CLI and tunnel directly to the Express or Flask server instead:

bash
ngrok http 3000
# Copy the ngrok URL and set it as your server URL

End-of-Call Report Fields

The end-of-call-report event includes:

FieldDescription
callFull call object with metadata
endedReasonWhy the call ended
artifactRecording, transcript, messages, and other enabled artifacts
analysisConfigured summaries, structured data, and success evaluation
costTotal call cost
startedAt / endedAtCall timing, when included

References

Additional Resources

Vapi provides a documentation MCP server that gives compatible AI agents access to the Vapi knowledge base. Use its documentation search for advanced configuration, troubleshooting, SDK details, and anything beyond this skill.

See the Vapi MCP integration guide for setup instructions across supported agents.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Setup Webhook AI skill do?

Configure Vapi server URLs and webhooks to receive real-time call events, transcripts, tool calls, and end-of-call reports. Use when setting up webhook endpoints, building tool servers, or integrating Vapi events into your application.

Why use Setup Webhook on TypingMind?

Because you install it once and use it with any model. Setup Webhook is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Setup Webhook in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VapiAI/skills/tree/main/plugins/vapi-voice-ai/skills/setup-webhook. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Setup Webhook?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Setup Webhook?

As many as you like. As long as a model supports skills, you can use Setup Webhook with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Setup Webhook AI skill free?

Yes. It is published on GitHub by VapiAI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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