Medium Risk

update_tool

Update an existing tool

Risk signalsHigh parameter count (10 properties)

Part of the Try server.

update_tool can modify Try data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use update_tool to create or modify resources in Try. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call update_tool repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Try.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_tool": {
      "limits": [
        {
          "counter": "update_tool_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Try policy for all 13 tools.

Get this rule live on your own Try server in minutes. PolicyLayer enforces it on every call, before it runs.

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View all 13 tools →

These attack patterns abuse exactly the kind of access update_tool gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so update_tool only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the update_tool tool do? +

Update an existing tool. It is categorised as a Write tool in the Try MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_tool? +

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

What risk level is update_tool? +

update_tool is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_tool? +

Yes. Add a rate_limit block to the update_tool 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 update_tool completely? +

Set action: deny in the PolicyLayer policy for update_tool. 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 update_tool? +

update_tool is provided by the Try MCP server (https://install.md/mcp/try). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Try tool call.

Deterministic rules across all 13 Try tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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