Back to Integrations
integration integration
integration HTTP Request Tool node

Integrate HTTP Request Tool with 500+ apps and services

Unlock HTTP Request Tool’s full potential with n8n, connecting it to similar AI apps and over 1000 other services. Automate AI workflows by integrating, training, and deploying models across various platforms. Create adaptable and scalable workflows between HTTP Request Tool and your stack. All within a building experience you will love.

Create workflows with HTTP Request Tool integrations

797 integrations
Sort by:
Popularity
NameOldestNewest

Popular ways to use HTTP Request Tool integration

Webhook node
Respond to Webhook node
+5

Voice Activated Multi-Agent Demo for Vagent.io using Notion and Google Calendar

Purpose Use a lightweight Voice Interface, for you and your entire organization, to interact with an AI Supervisor, a personal AI Assistant, which has access to your custom workflows. You can also connect the supervisor to your already existing Agents. Demo & Explanation How it works After recording a message in the Vagent App, it gets transcribed and sent in combination with a session ID to the registered webhook The Main Agent acts as a router. I interprets the message while using the stored chat history (bound to the session ID) and chooses which tool to use to perform the required action and. Tools on this level are workflows, which contain subordinated Agents. Since the Main Agent interprets the original message, the raw input is passed to the Tools/Sub-Agents as a separate parameter Within the Sub-Agents the actual processing takes place. Each of those has it’s separate chat memory (with a suffix to the main session ID), to achieve a clear separation of concerns Depending on the required action an HTTP Request Tool is called. The result is being formatted in Markdown and returned to the Main Agent with an additional short prompt, so it does not get interpreted by the Main Agent. Drafts are separated from a short message by added indentation (angle brackets). If some information is missing, no tool is called just yet, instead a message is returned back to the user The Main Agent then outputs the result from the called Sub-Agent. If a draft is included, it gets separated from the spoken output Finally the formatted output is returned as response to the webhook. The message is split into a spoken and a text version, which enables the App to read out loud unnecessary information like drafts in this example See the full documentation of Vagent: https://vagent.io/docs Setup Import this workflow into your n8n instance Follow the instructions given in the sticky notes on the canvas Setup your credentials. OpenAI can be replaced by another LLM in the workflow, but is required for the App to work. Google Calendar and Notion are required for all scenarios to work Copy the Webhook URL from the Webhook node of the main workflow Download the Vagent App from https://vagent.io In the settings paste your OpenAI API Token, the Webhook URL and the password defined for Header Auth Now you can use the App to interact with the Multi-Agent using your Voice by tapping the Mic symbol in the App to record your message. To use the chat trigger (for testing) properly, temporarily disable the nodes after the Tools Agent.
octionic
Mario
Airtable node
Twilio node
+7

Handling Appointment Leads and Follow-up With Twilio, Cal.com and AI

This n8n workflow builds an appointment scheduling AI agent which can Take enquiries from prospective customers and help them book an appointment by checking appointment availability Where no appointment is booked, the Agent is able to send follow-up messages to re-engage leads. After an appointment is booked, the agent is able reschedule or even cancel the booking for the user without human intervention. For small outfits, this workflow could contribute the necessary "man-power" required to increase business sales. The sample Airtable can be found here: https://airtable.com/appO2nHiT9XPuGrjN/shroSFT2yjf87XAox 2024-10-22 Updated to Cal.com API v2. How it works The customer sends an enquiry via SMS to trigger our workflow. For this trigger, we'll use a Twilio webhook. The prospective or existing customer's number is logged in an Airtable Base which we'll be using to track all our enquries. Next, the message is sent to our AI Agent who can reply to the user and decide if an appointment booking can be made. The reply is made via SMS using Twilio. A scheduled trigger which runs every day, checks our chat logs for a list of prospective customers who have yet to book an appointment but still show interest. This list is sent to our AI Agent to formulate a personalised follow-up message to each lead and ask them if they want to continue with the booking. The follow-up interaction is logged so as to not to send too many messages to the customer. Requirements A Twilio account to receive customer messages. An Airtable account and Base to use as our datastore for enquiries. Cal.com account to use as our scheduling service. OpenAI account for our AI model. Customising this workflow Not using Airtable? Swap this out for your CRM of choice such as hubspot or your own service. Not using Cal.com? Swap this out for API-enabled services such as Acuity Scheduling or your own service.
jimleuk
Jimleuk
Notion node
OpenAI Chat Model node
+3

Notion knowledge base AI assistant

Who is this for This workflow is perfect for teams and individuals who manage extensive data in Notion and need a quick, AI-powered way to interact with their databases. If you're looking to streamline your knowledge management, automate searches, and get faster insights from your Notion databases, this workflow is for you. It’s ideal for support teams, project managers, or anyone who needs to query specific data across multiple records or within individual pages of their Notion setup. Check out the Notion template this Assistant is set up to use: https://www.notion.so/templates/knowledge-base-ai-assistant-with-n8n How it works The Notion Database Assistant uses an AI Agent built with Retrieval-Augmented Generation (RAG) to query this Knowledge Base style Notion database. The assistant can search across multiple properties like tags or question and retrieves content from inside individual Notion pages for additional context. Key features include: Querying the database with flexible filters. Searching within individual Notion pages and extracting relevant blocks. Providing a reference link to the exact Notion pages used to inform its responses, ensuring transparency and easy verification. This assistant uses two HTTP request tools—one for querying the Notion database and another for pulling data from within specific pages. It streamlines knowledge retrieval, offering a conversational, AI-driven way to interact with large datasets. Set up Find basic set up instructions inside the workflow itself or watch a quickstart video 👇
max-n8n
Max Tkacz
HTTP Request node
Slack node
Webhook node
+17

Advanced AI Demo (Presented at AI Developers #14 meetup)

This workflow was presented at the AI Developers meet up in San Fransico on 24 July, 2024. AI workflows Categorize incoming Gmail emails and assign custom Gmail labels. This example uses the Text Classifier node, simplifying this usecase. Ingest a PDF into a Pinecone vector store and chat with it (RAG example) AI Agent example showcasing the HTTP Request tool. We teach the agent how to check availability on a Google Calendar and book an appointment.
max-n8n
Max Tkacz
HTTP Request Tool node

About HTTP Request Tool

Related categories

Similar integrations

  • Wikipedia node
  • OpenAI Chat Model node
  • Zep Vector Store node
  • Postgres Chat Memory node
  • Pinecone Vector Store node
  • Embeddings OpenAI node
  • Supabase: Insert node
  • OpenAI node

Over 3000 companies switch to n8n every single week

Connect HTTP Request Tool with your company’s tech stack and create automation workflows

Last week I automated much of the back office work for a small design studio in less than 8hrs and I am still mind-blown about it.

n8n is a game-changer and should be known by all SMBs and even enterprise companies.

in other news I installed @n8n_io tonight and holy moly it’s good

it’s compatible with EVERYTHING

We're using the @n8n_io cloud for our internal automation tasks since the beta started. It's awesome! Also, support is super fast and always helpful. 🤗

FAQ about HTTP Request Tool integrations

  • How can I set up HTTP Request Tool integration in n8n?

      To use HTTP Request Tool integration in n8n, start by adding the HTTP Request Tool node to your workflow. You'll need to authenticate your HTTP Request Tool account using supported authentication methods. Once connected, you can choose from the list of supported actions or make custom API calls via the HTTP Request node, for example: you can select actions such as sending requests or retrieving data from your HTTP Request Tool account. Additionally, ensure you configure any necessary parameters and headers according to the API specifications. After setting everything up, you can execute the workflow to see the integration in action.

  • Do I need any special permissions or API keys to integrate HTTP Request Tool with n8n?

  • Can I combine HTTP Request Tool with other apps in n8n workflows?

  • What are some common use cases for HTTP Request Tool integrations with n8n?

  • How does n8n’s pricing model benefit me when integrating HTTP Request Tool?

Implement complex processes faster with n8n

red icon yellow icon red icon yellow icon