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.
Best use case
setup-webhook is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using setup-webhook should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/setup-webhook/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How setup-webhook Compares
| Feature / Agent | setup-webhook | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this 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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 '{
"serverUrl": "https://your-server.com/vapi/webhook",
"serverUrlSecret": "your-webhook-secret"
}'
```
### On a Phone Number
```bash
curl -X PATCH https://api.vapi.ai/phone-number/{id} \
-H "Authorization: Bearer $VAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"serverUrl": "https://your-server.com/vapi/webhook"
}'
```
### 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
| Event | Description | Expects Response? |
|-------|-------------|-------------------|
| `assistant-request` | Request for dynamic assistant config | Yes — return assistant config |
| `tool-calls` | Assistant is calling a tool | Yes — return tool results |
| `status-update` | Call status changed | No |
| `transcript` | Real-time transcript update | No |
| `end-of-call-report` | Call completed with summary | No |
| `hang` | Assistant failed to respond | No |
| `speech-update` | Speech activity detected | No |
## Webhook Server Example (Express.js)
```typescript
import express from "express";
import crypto from "crypto";
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 ${message.call.customer?.name || "there"}!`,
model: {
provider: "openai",
model: "gpt-4.1",
messages: [
{ role: "system", content: "You are a helpful assistant." },
],
},
voice: { provider: "vapi", voiceId: "Elliot" },
transcriber: { provider: "deepgram", model: "nova-3", language: "en" },
},
});
break;
case "tool-calls":
// Handle tool calls from the assistant
const results = message.toolCallList.map((toolCall: any) => ({
toolCallId: toolCall.id,
result: handleToolCall(toolCall.name, toolCall.arguments),
}));
res.json({ results });
break;
case "end-of-call-report":
// Process the call report
console.log("Call ended:", {
callId: message.call.id,
duration: message.durationSeconds,
cost: message.cost,
summary: message.summary,
transcript: message.transcript,
});
res.json({});
break;
case "status-update":
console.log("Call status:", message.status);
res.json({});
break;
case "transcript":
console.log(`[${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"},
"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('summary')}")
return jsonify({})
if __name__ == "__main__":
app.run(port=3000)
```
## Webhook Authentication
Verify webhook authenticity using the secret:
```typescript
function verifyWebhook(req: express.Request, secret: string): boolean {
const signature = req.headers["x-vapi-signature"] as string;
if (!signature || !secret) return false;
const payload = JSON.stringify(req.body);
const expected = crypto
.createHmac("sha256", secret)
.update(payload)
.digest("hex");
return crypto.timingSafeEqual(
Buffer.from(signature),
Buffer.from(expected)
);
}
```
## Local Development
Use the Vapi CLI to forward webhooks to your local server:
```bash
# Install the CLI
curl -sSL https://vapi.ai/install.sh | bash
# Forward events to local server
vapi listen --forward-to localhost:3000/vapi/webhook
```
Or use ngrok:
```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:
| Field | Description |
|-------|-------------|
| `call` | Full call object with metadata |
| `transcript` | Complete conversation transcript |
| `summary` | AI-generated call summary |
| `recordingUrl` | URL to the call recording |
| `durationSeconds` | Call duration |
| `cost` | Total call cost |
| `costBreakdown` | Breakdown by component (STT, LLM, TTS, transport) |
| `messages` | Array of all conversation messages |
## References
- [Server URL Events](references/webhook-events.md) — All event types with payload schemas
- [Vapi Server URL Docs](https://docs.vapi.ai/server-url) — Official documentation
- [Local Development](https://docs.vapi.ai/server-url/developing-locally) — Testing webhooks locally
## Additional Resources
This skills repository includes a **Vapi documentation MCP server** (`vapi-docs`) that gives your AI agent access to the full Vapi knowledge base. Use the `searchDocs` tool to look up anything beyond what this skill covers — advanced configuration, troubleshooting, SDK details, and more.
**Auto-configured:** If you cloned or installed these skills, the MCP server is already configured via `.mcp.json` (Claude Code), `.cursor/mcp.json` (Cursor), or `.vscode/mcp.json` (VS Code Copilot).
**Manual setup:** If your agent doesn't auto-detect the config, run:
```bash
claude mcp add vapi-docs -- npx -y mcp-remote https://docs.vapi.ai/_mcp/server
```
See the [README](../README.md#vapi-documentation-server-mcp) for full setup instructions across all supported agents.Related Skills
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