Cookbook
Agents & skills · for AI agents

Built-in tools (and the system MCP)

The tools the platform ships — lead capture, documents, follow-ups, web search — plus the auto-installed time/weather/location server.

MCP tools:list_toolsupdate_agent

You don't have to build the common tools — the platform ships them. Attach the ones this agent's job needs with update_agent(name, tools=[…]); keep the set small (see Design principles). Always confirm the exact names on your tenant with list_tools() — that is the source of truth.

The built-in tools

ToolWhat it does
web_searchLook something up on the open web.
save_contactCapture the end user's contact details into their profile — the platform's lead-capture / records path.
export_documentGenerate a structured document (a branded summary / report) for the conversation.
schedule_followupProactively follow up later ("check back in 2 days") — the message is sent for you.
schedule_reminderSet a reminder for the end user; list_reminders / cancel_reminder manage them.

load_skill is also built in, but you don't attach it — the model pulls a skill on its own when a skill's description matches.

list_tools()                                              # exact names available on your tenant
update_agent(name="Support", tools=["web_search", "save_contact", "schedule_followup"])

Capturing a contact with save_contact populates the user's record; combined with ask_forms on the agent, structured intake lands as records you can review in the console.

The system MCP — already installed

Every tenant gets a built-in system MCP server, enabled by default, with keyless tools for local time, weather, and IP geolocation (city / region / timezone). You don't register it — it's there. Its tools show up in list_tools() alongside the built-ins above, ready to attach.

So "what's the weather where the user is?" or "what's their local time?" work out of the box — the platform injects the end user's client IP, so location-aware answers need no setup.