Medium Risk

configure_project

Sets platform-specific configuration (iOS bundle ID, Android package name, deeplink schemas, SHA-256 fingerprints).

Part of the Ulinkly server.

configure_project can modify Ulinkly 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 configure_project to create or modify resources in Ulinkly. 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 configure_project 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 Ulinkly.

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

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

See the full Ulinkly policy for all 21 tools.

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These attack patterns abuse exactly the kind of access configure_project 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 configure_project 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 configure_project tool do? +

Sets platform-specific configuration (iOS bundle ID, Android package name, deeplink schemas, SHA-256 fingerprints).. It is categorised as a Write tool in the Ulinkly MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on configure_project? +

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

What risk level is configure_project? +

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

Can I rate-limit configure_project? +

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

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

configure_project is provided by the Ulinkly MCP server (@ulinkly/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Ulinkly tool call.

Deterministic rules across all 21 Ulinkly 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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