Integration: guides & tutorials

Chatbase YouTube Connector is a free, MIT-licensed tool that keeps a Chatbase AI agent trained on your YouTube channel, so the agent answers customers from your videos and links to the exact minute it used. It runs as a scheduled GitHub Action or a Docker container on any VPS, with no server or database of its own. Transcripts come from an Apify Actor at about $1 per 1,000 videos, and a day with no new uploads costs $0. On Chatbase Standard and above it syncs through the API; on Free and Hobby it exports ready-to-upload files instead.

Here is what a customer sees once it is running:

Customer: How do I hand a chat over to a human? Agent: Turn on the Chatbase live chat action, then ... watch at 0:24

The Chatbase API lets your own backend work with a Chatbase AI agent: send messages and stream replies, read and search conversations, manage knowledge sources, create and answer Helpdesk tickets, and start real-time voice sessions. It requires the Standard plan or above: $150/month billed monthly, or $120/month billed annually ($1,440/year), with 4,000 message credits per month that API calls share with the chat widget. Free and Hobby workspaces get a 403. Prices verified on chatbase.co/pricing on 2026-10-04.

Prerequisite: a Standard (or higher) workspace. Compare Chatbase plans with API access, or read our Chatbase pricing breakdown first. Each reply costs credits based on the AI model the agent uses (see Best Practices).

Chatbase ships two REST API versions. API v1 is the original integration path; API v2 is a redesign with structured error codes, cursor-based pagination, Server-Sent Events (SSE) streaming, a cleaner response contract, and endpoints for agents, knowledge sources, the Helpdesk, and voice. This guide covers v2 only, since it is the forward path for new integrations in 2026. The agent you call is the same one you configure in the dashboard, with its knowledge, instructions, actions, and procedures.

Model Context Protocol (MCP) is an open standard for how an AI host (IDE, desktop assistant, or similar) discovers and calls tools in a separate MCP server over transports such as stdio (local) or HTTP (remote). It is a JSON-RPC bridge that standardizes the boundary where models meet APIs, files, and automation. It does not replace your databases or scrapers. The payoff is one reusable integration surface across MCP-capable hosts, provided you still own auth, timeouts, and least privilege.

Below we split what the spec actually defines from what each vendor ships, sketch how the ecosystem shows up in scraping and data workflows, and outline adoption so a chat session does not become root access. For headline news context, see Top 10 AI and tech stories this week (March 17–24, 2026).

Bright Data offers residential, datacenter, ISP, and mobile proxy products behind a single Super Proxy hostname. Correct zone choice and credential format prevent surprise bills (residential is priced per GB) and avoid blocked or unsupported destinations.

This post is a practical setup path: pick a network, provision a zone, verify connectivity, then wire Python, Node.js, or cURL. For teams that do not want to own retry logic and browser farms, Apify is a common managed alternative—Bright Data and Apify are often used together when you need custom proxy pools inside your own code.

n8n is a workflow automation tool that pairs well with Apify because it handles long-running jobs, large JSON payloads, and branching logic without the tight synchronous limits of simpler connectors. This guide covers setup, the official Apify node, webhook patterns for slow Actors, example workflows, and operational tips.