Make

About Make

The Make brand covers a visual automation platform that combines scenario-based workflows, more than 3,000 pre-built app connections, AI tools, AI Agents, Model Context Protocol connectivity, observability and enterprise governance. This page focuses on how those product capabilities fit together. Corporate ownership and company history belong on the Make company page, while detailed AI Agent behavior and credit usage belong on the relevant product page.

How is the Make automation platform organized?

Make's core is the visual Scenario Builder. Users connect modules, triggers, routers, filters, webhooks, APIs and data transformations into workflows that can run on schedules or in response to events. The visual canvas is designed to show how data moves between systems rather than hiding workflow logic behind a list of steps.

The wider platform now extends beyond classic workflow automation. Current Make product materials highlight AI Agents, Maia by Make, Make AI tools, MCP Server and Client capabilities, Make Grid, an Analytics Dashboard, role-based controls and a catalogue of more than 3,000 pre-built apps. These capabilities share the same automation environment, so teams can combine conventional rules with AI reasoning instead of maintaining separate automation and agent stacks.

Where do AI Agents fit within the Make range?

Make AI Agents are designed to sit inside the Scenario Builder rather than operate as an isolated chatbot product. The current generation can use prompts, knowledge and tools, call connected systems and expose reasoning and execution information inside the same visual environment as ordinary scenarios. Agents can also be reused across workflows.

The practical distinction is that deterministic modules are better for fixed rules, while agents are intended for work that needs interpretation, tool selection or judgment. Make's own guidance recommends combining the two approaches. That keeps predictable process steps under explicit workflow control while using agents only where flexible reasoning adds value.

What role does MCP play in Make?

Make supports both MCP Server and MCP Client patterns. MCP Server can expose selected Make scenarios as tools that compatible AI systems such as ChatGPT, Claude or Cursor can call. MCP Client lets a Make scenario or agent call tools hosted on external MCP servers.

This makes MCP part of Make's broader orchestration strategy rather than a separate automation product. Teams can keep sensitive business logic inside a controlled Make scenario, expose only the required inputs and outputs, and decide which workflows an external agent is allowed to trigger. That can be safer than giving an agent unrestricted access to a full application API, but administrators still need to control tokens, scenario permissions and downstream credentials.

How does Make pricing work across the portfolio?

Make uses a credit-based commercial model. Most normal module actions consume one credit per operation, while some built-in AI features can use dynamic credits based on token consumption or other processing factors. This means the cost of the platform depends on both the subscription tier and how frequently workflows or agents run.

Current public plans include Free, Core, Pro, Teams and Enterprise. At the 10,000-credit monthly level, Make currently lists Core at $12 per month, Pro at $21 and Teams at $38 on the monthly pricing view, while Enterprise uses custom pricing. Annual billing can reduce the effective rate. Exact plan pricing and credit allowances should be checked before purchase because usage tiers and AI consumption can materially change the total.

What does Make provide for larger teams and enterprises?

Higher tiers add capabilities aimed at collaboration, administration and scale. Current product and pricing pages describe team roles, template sharing, priority execution, custom variables, API access, enterprise integrations, custom functions, advanced security, 24/7 enterprise support and overage protection depending on plan.

Make also publishes security and privacy information covering GDPR, SOC 2 Type II, SOC 3, encryption and single sign-on. Those controls are important because a single automation platform may hold credentials and write access across CRM, finance, support, marketing and internal systems. Enterprises should review permission design, connection ownership, auditability and data-processing terms before centralizing critical workflows.

Who is the Make portfolio best suited for?

Make is best suited to teams that need to connect many cloud applications, APIs and business processes while keeping workflow logic visible to non-developers and technical operators alike. It can be especially useful where processes combine straightforward rules with AI-assisted classification, research or routing.

A simpler automation tool may be easier when workflows are short and predictable. A code-first integration platform may be better when engineers need full control over runtime, testing and deployment. The reason to standardize on Make should be the value of its visual orchestration, connector breadth and shared governance, not simply the number of available modules.