Integrations

Connect channels, credentials, and MCP tools that workflows use at runtime.

The Integrations section connects Hexabot to external entrypoints and services.

Use it to receive inbound traffic, store shared secrets, and expose external tools to AI actions.

Open it from Integrations in the admin panel.

What you manage here

Integrations is organized into three areas:

• Channels and Sources define how conversations enter Hexabot and which workflow handles them.

• MCP Servers connect external Model Context Protocol tools to AI actions.

• Credentials store named secrets that integrations and bindings can reference safely.

Each part solves a different integration need, but they are designed to work together.

How integrations fit into workflows

Most integrations support one of these runtime paths:

1. A channel source receives an inbound event.

2. Hexabot routes that event to a workflow.

3. The workflow uses credentials, MCP tools, or both while it runs.

Common examples:

• A web source receives a user message and starts a conversational workflow.

• An AI task uses an MCP server to call external tools during reasoning.

• A model binding or HTTP service uses a stored credential instead of a pasted secret.

Choose the right integration type

Use Channels and Sources when you need an entrypoint.

Use it for:

• web widgets;

• channel-specific inbound traffic;

• separate sources for environments, brands, or workflows.

Use Credentials when you need a reusable secret.

Use it for:

• API keys;

• bearer tokens;

• shared secrets selected by name in forms and bindings.

Use MCP Servers when an AI action needs external tools.

Use it for:

• remote MCP services over HTTP;

• local MCP commands over stdio;

• tool discovery and allow-listed tool access in AI workflows.

Typical setup

For most teams, setup follows a simple order:

1. Create a Credential if the integration needs authentication.

2. Configure a Channel Source to receive traffic, or an MCP Server to provide tools.

3. Reference that integration from your workflow configuration or binding.

4. Test the flow before relying on it in production.

Best practices

• Keep source names clear and environment-specific.

• Store secrets in credentials, not in workflow definitions.

• Prefer editing credentials for secret rotation.

• Limit AI tools to the MCP server and tool names a workflow actually needs.

• Disable unused sources or servers instead of deleting them immediately.