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Webhooks let you trigger an Xpander agent from any system that can make an HTTP request, including automation platforms like Zapier, form submissions, CI/CD pipelines, or your own applications. Once set up, you can:
  • Trigger an agent run from any inbound HTTP POST with a prompt or payload
  • Choose synchronous (wait for the agent’s response) or asynchronous (fire-and-forget) invocation
  • Upload files (documents, images, audio) alongside the prompt
  • Extract specific fields from the agent’s response instead of returning the full payload
  • Map nested fields from the incoming payload to the agent’s input parameters
  • Pass through MCP OAuth tokens for downstream tool authentication
Pre-requisites:

Enable Webhooks

1

Open the Channels tab

In the Agent Studio, click the gear icon and go to the Channels tab. Find the Webhook section and toggle it on.
Channels tab with the Webhook section showing the Enabled toggle and Configure and test button
2

Open the tester

Click Configure and test to open the Agent Webhook Tester. This shows your Payload URL (with agent ID and API key embedded) and a ready-to-use cURL command.
Agent Webhook Tester showing payload URL, API key, cURL command, JSON payload fields, and Test Webhook button
3

Test it

Choose an input format - JSON, Form Data, or Multipart. Set your payload fields and click Test Webhook. The response appears in the Response History panel.

Make Requests

All webhook requests are POST requests to https://webhook.xpander.ai/ with your agent ID and API key.

Required Parameters

Optional Parameters

You can include any additional fields in your request body - they’re all passed to the agent as context.
When the same parameter appears in multiple places, query parameters take priority over body parameters, which take priority over defaults.

Choose Sync vs Async

Synchronous (default) - The request blocks until the agent finishes and returns the full result. Best for short tasks and interactive workflows.
Asynchronous - Set asynchronous=true to return immediately. The agent processes in the background. Best for long-running tasks, file processing, or when you don’t need the result inline.

Upload Files

Upload files using multipart/form-data. The agent automatically processes them - OCR for images, text extraction for PDFs, transcription for audio.
Supported types: PDF, DOC, DOCX, TXT, XLS, XLSX, CSV, PNG, JPEG, GIF, WEBP, SVG, ZIP.
Files must be uploaded directly - URLs to external files are not supported. The webhook needs the actual file content.
For large batches (10+ files), use async mode and break uploads into batches of 5-10 files.
Uploaded files are stored on the Xpander platform and exposed to your agent through secure presigned URLs. Those URLs are scoped to your organization’s agents and remain valid for 30 days after upload. Your agent never handles download or storage logic directly.

Extract Data from Responses

Use the getter parameter to extract a specific field from the agent’s response using dot notation.
Instead of the full response object, this returns just the extracted value:

Map Dynamic Parameters

Use params_mapping as a query parameter to extract values from nested payload fields and map them to webhook parameters. This is especially useful for integrations with Telegram bots, WhatsApp, and other messaging platforms where identifiers are nested.
The mapping uses dot notation to navigate nested fields. It supports all standard parameters: task_id, user_id, user_email, user_first_name, user_last_name, prompt.

Pass MCP OAuth Tokens

If your agent uses MCP servers with OAuth authentication, pass pre-authenticated user tokens via user_tokens to bypass the interactive OAuth flow during webhook execution.
To find the graph item IDs for your MCP servers, call the Get Agent API and inspect graph.items for entries with type: "mcp".

Monitor Webhook Runs

Every webhook invocation creates a task visible in the Monitor tab, exactly like any other agent run. You get the full execution trace: prompts, tool calls with request/response payloads, files processed, timing, and token usage. For details on reading execution traces, see Threads.

Handle Errors

Next Steps

Scheduled Tasks

Run agents on a recurring schedule

MCP Protocol

Expose agents to Claude Desktop and code editors

Monitor Runs

Trace execution, debug failures, and review AI performance