schedule_demo
Book a product demo with Adrata. Free tier — no account needed. Creates a calendar event via Cal.com. The attendee receives an email confirmation automatically.
This record as markdown: /tools/adrata-adrata-mcp/schedule-demo.md
What schedule_demo does on Adrata
AI agents use schedule_demo to create or update resources in Adrata, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Adrata environment.
Why schedule_demo is rated Medium
An AI agent can call schedule_demo faster than any human can review: one bad instruction and it creates or modifies resources in Adrata by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs schedule_demo safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Adrata, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For schedule_demo, this is the rule to start with:
schedule_demo stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Adrata, apply this rule, and every schedule_demo call is checked against it from then on.
Questions about schedule_demo
Book a product demo with Adrata. Free tier — no account needed. Creates a calendar event via Cal.com. The attendee receives an email confirmation automatically. It is categorised as a Write tool in the Adrata MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Adrata MCP server in PolicyLayer and add a rule for schedule_demo: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Adrata. Nothing to install.
schedule_demo is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the schedule_demo rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for schedule_demo. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
schedule_demo is provided by the Adrata MCP server (@adrata/adrata-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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