Requests to the GHL Contacts API require authorization. Use your GHL API credentials or an OAuth token to authenticate calls from your Azure OpenAI integration and rotate credentials regularly for security.
Azure OpenAI should authenticate to the GHL API with a secure secret stored in your vault. Use token-based authentication, follow principle of least privilege, and monitor token usage.
GET /contacts/:contactId, GET /contacts/:contactId/tasks, GET /contacts/:contactId/tasks/:taskId, GET /contacts/:contactId/notes, GET /contacts/:contactId/notes/:id, GET /contacts/:contactId/appointments, GET /contacts/, GET /contacts/business/:businessId, POST /contacts/, PUT /contacts/:contactId, DELETE /contacts/:contactId, POST /contacts/:contactId/tasks, PUT /contacts/:contactId/tasks/:taskId, PUT /contacts/:contactId/tasks/:taskId/completed, DELETE /contacts/:contactId/tasks/:taskId, POST /contacts/:contactId/tags
Trigger: A user asks for a specific contact detail or activity; Azure OpenAI issues targeted GET requests like GET /contacts/:contactId, GET /contacts/:contactId/tasks, and GET /contacts/:contactId/notes to populate a response.
Actions: Retrieve the primary contact record, then fetch related tasks, notes, or appointments as needed to assemble a complete answer.
Methods and paths used: GET /contacts/:contactId, GET /contacts/:contactId/tasks, GET /contacts/:contactId/notes, GET /contacts/:contactId/appointments.
Key fields: contactId, taskId, noteId, appointmentId, businessId.
Trigger: Periodic data sync to refresh AI context or on-demand bulk lookups for user prompts.
Actions: Use POST /contacts/ to bulk-create, PUT /contacts/:contactId to update, and batch GET calls to retrieve multiple records in one flow.
Methods and paths: POST /contacts/, PUT /contacts/:contactId, GET /contacts/, GET /contacts/business/:businessId.
Key fields: contactId, businessId, tag, status.
Trigger: A GHL or app event fires (contact updated, new task, etc.). Azure OpenAI responds by querying updated data or syncing state.
Actions: Update local AI context, pull latest notes and tasks, or push updates back to GHL when needed.
Methods and paths: POST /contacts/:contactId/tasks (to create), PUT /contacts/:contactId/tasks/:taskId (to update), PUT /contacts/:contactId/tasks/:taskId/completed (to mark done).
Key fields: contactId, taskId, id (notes), eventId.
Build AI-powered workflows without writing code by linking Azure OpenAI prompts directly to GHL Contacts API calls.
Leverage the Zapier App Connector style experience to automate CRM tasks inside AI-driven chats.
Maintain a single source of truth for contact data in prompts, prompts results, and downstream automations.
Key elements include authentication, endpoints, data objects (contacts, tasks, notes), and the AI prompts that orchestrate calls. Processes cover credential storage, request crafting, error handling, and monitoring.
A URL path in the GHL Contacts API used to perform an action such as retrieving a contact or updating a record.
The credentials (API key or OAuth token) that authorize calls from Azure OpenAI to the GHL API.
A message pushed from GHL to your app or vice versa to signal an event and trigger a flow.
The maximum number of requests allowed within a time window to protect the API and ensure fair usage.
Ask the AI to summarize a contact’s history, notes, and upcoming tasks using data pulled from the Contacts API for richer dialogue.
Let the AI fetch tasks and suggest next actions based on due dates and status.
Generate personalized follow-ups based on contact activity and notes, then trigger reminders in your CRM.
Obtain an API key or OAuth token, store it securely, and grant Azure OpenAI access to GHL.
Enable the endpoints you plan to use (for example GET /contacts/:contactId) and set scopes like contacts.readonly.
Run tests, verify AI outputs, and monitor for errors and rate limits.
You authenticate using an API key or OAuth token; store credentials securely and rotate them regularly. Use least-privilege permissions for your Azure OpenAI integration. If a token expires, refresh it and retry the request. Ensure your requests include appropriate scopes like contacts.readonly.
Common endpoints include GET /contacts/:contactId and GET /contacts/:contactId/tasks for context in a chat. For bulk updates, use POST /contacts/ and PUT /contacts/:contactId. Batch calls reduce latency in prompts.
Plan a regular sync: schedule background jobs to pull updated contacts, tasks, notes, and appointments. Maintain a local cache and invalidate stale data. Use webhooks to trigger updates when data changes.
No-code patterns are available if you use connector platforms like the App Connector style. You can also rely on your AI prompts to orchestrate API calls without writing application code.
Rate limits vary by plan and endpoint. Design prompts to handle partial data and implement retries with exponential backoff. Spread requests over time to avoid bursts.
Implement retry logic on errors, capture error codes, and provide clear user messages. Log failed calls and monitor for token expiry or permission issues. Use idempotent endpoints where possible.
Look for templates that cover authentication, endpoint access, error handling, and data mapping. Build prompts that request specific fields and then map results to your UX.
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Complete Operations Catalog - 126 Actions & Triggers
