destination_point · TinyFn MCP: Risk & Policy

WHAT IT DOES

What destination_point does on TinyFn

AI agents invoke destination_point to trigger actions in TinyFn. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

PARAMETERS

Parameter	Type	Required	Description
`lat`	number	Yes	Starting latitude
`lon`	number	Yes	Starting longitude
`unit`	string	—	Unit: km or mi
`bearing`	number	Yes	Bearing in degrees
`distance`	number	Yes	Distance to travel

Parameters from the server's own tool schema.

WHY IT NEEDS A POLICY

Why destination_point needs a policy

destination_point triggers real processes with real consequences. An agent gone sideways doesn't fire it once — it starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

destination_point Rate-limited

destination_point stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "destination_point": {
      "limits": [
        {
          "counter": "destination_point_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches TinyFn, so you can run agents against it safely.

FAQ

Questions about destination_point

What does the destination_point tool do? +

Calculate destination point given start, bearing, and distance. It is categorised as a Execute tool in the TinyFn MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does destination_point accept? +

destination_point accepts 5 parameters: lat, lon, unit, bearing, distance. Required: lat, lon, bearing, distance. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on destination_point? +

Register the TinyFn MCP server in PolicyLayer and add a rule for destination_point: 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 TinyFn. Nothing to install.

What risk level is destination_point? +

destination_point is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit destination_point? +

Yes. Add a rate_limit block to the destination_point 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.

How do I block destination_point completely? +

Set action: deny in the PolicyLayer policy for destination_point. 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.

What MCP server provides destination_point? +

destination_point is provided by the TinyFn MCP server (https://api.tinyfn.io/mcp/all/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.