validate_custom · Project Management AI Analysis MCP

WHAT IT DOES

What validate_custom does on Project Management AI Analysis

AI agents invoke validate_custom to trigger actions in Project Management AI Analysis. 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.

WHY IT NEEDS A POLICY

Why validate_custom needs a policy

The tool executes arbitrary, user-defined validation rules, meaning its behavior depends entirely on the conditions provided. This is analogous to running user-supplied scripts or queries. While it is framed as 'validation,' executing custom/user-defined logic is an Execute-category action.

From the tool's definition 'Run custom validation rules defined by the user' — actively executes user-defined logic/rules against data

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

validate_custom Rate-limited

validate_custom 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": {
    "validate_custom": {
      "limits": [
        {
          "counter": "validate_custom_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 Project Management AI Analysis, so you can run agents against it safely.

FAQ

Questions about validate_custom

What does the validate_custom tool do? +

Run custom validation rules defined by the user. Supports multiple condition types for organization-specific requirements. It is categorised as a Execute tool in the Project Management AI Analysis MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on validate_custom? +

Register the Project Management AI Analysis MCP server in PolicyLayer and add a rule for validate_custom: 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 Project Management AI Analysis. Nothing to install.

What risk level is validate_custom? +

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

Can I rate-limit validate_custom? +

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

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

validate_custom is provided by the Project Management AI Analysis MCP server (pm-mcp-servers). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.