Low Risk

decision

Structured decision intelligence with confidence scoring. Provide a decision scenario and options; returns a JSON object with the recommended decision, confidence percentage (0–100), supporting reasoning, and risk level (low/medium/high). Use when you need a structured, actionable output rather t...

Part of the Invinoveritas server.

decision is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

SECURE INVINOVERITAS →

Free to start. No card required.

AI agents call decision to retrieve information from Invinoveritas without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though decision only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "decision": {}
  }
}

See the full Invinoveritas policy for all 26 tools.

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

ENFORCE ON MY INVINOVERITAS →

View all 26 tools →

These attack patterns abuse exactly the kind of access decision 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 decision only ever does what you allow.

SECURE INVINOVERITAS →

Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the decision tool do? +

Structured decision intelligence with confidence scoring. Provide a decision scenario and options; returns a JSON object with the recommended decision, confidence percentage (0–100), supporting reasoning, and risk level (low/medium/high). Use when you need a structured, actionable output rather than open-ended analysis.. It is categorised as a Read tool in the Invinoveritas MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on decision? +

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

What risk level is decision? +

decision is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit decision? +

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

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

decision is provided by the Invinoveritas MCP server (https://api.babyblueviper.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Invinoveritas tool call.

Deterministic rules across all 26 Invinoveritas tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

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

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.