Prompt injection and system-prompt extraction testing for LLM agents. Free 8-probe sample.
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PRO pricing & payment info: 44 probes / 20 attack classes / 0-100 score / CI gate / per-class remediation, 0.15 XNO (ERC-20 or Lightning) or card.
This tool takes no arguments.
This tool isn't marked read-only, so it may change something on the server or in an account you connected.
Pick your client. Values in capitals, like YOUR_TOKEN, are yours to fill in.
claude mcp add --transport http mcp-prompt-injection https://llmrt-companion.manhliemcn4euwlu.workers.dev/mcp-prompt-injection
PRO pricing & payment info: 44 probes / 20 attack classes / 0-100 score / CI gate / per-class remediation, 0.15 XNO (ERC-20 or Lightning) or card.
No arguments.
{
"type": "object",
"properties": {}
}Machine-readable autonomous purchase procedure: how an agent pays (0.15 XNO, or USDC on Base via x402) and receives the PRO download with no human in the loop (callback push + poll fallback).
No arguments.
{
"type": "object",
"properties": {}
}Poll a scan by job id (returned by run_free_scan) until status=done.
| Argument | Type | Description |
|---|---|---|
| job_id* | string |
{
"type": "object",
"required": [
"job_id"
],
"properties": {
"job_id": {
"type": "string"
}
}
}Free LLM agent security review in ~35s. Two parts: (1) 8 live adversarial probes (jailbreak / prompt injection / system-prompt extraction / tool abuse) against your agent spec, and (2) a deterministic static audit of which guardrails the spec text itself is missing. Returns a 0-100 risk score, per-finding evidence, and a paste-ready guardrail sentence for each gap.
| Argument | Type | Description |
|---|---|---|
| spec* | string | Your agent / system prompt (>=20 chars) |
{
"type": "object",
"required": [
"spec"
],
"properties": {
"spec": {
"type": "string",
"description": "Your agent / system prompt (>=20 chars)"
}
}
}Judge one delivery against the task's own acceptance rule and return {verdict: accepted|rejected, reason}. Called by the brick.blue hub when this seat is drawn as validator. Judges only machine-checkable criteria (json_schema / contains / fields); a task with no such rule is accepted, because rejecting needs evidence.
| Argument | Type | Description |
|---|---|---|
| input | any | |
| title | string | |
| result | any | |
| taskId | string | |
| attemptId | string | |
| description | string |
{
"type": "object",
"required": [],
"properties": {
"input": {},
"title": {
"type": "string"
},
"result": {},
"taskId": {
"type": "string"
},
"attemptId": {
"type": "string"
},
"description": {
"type": "string"
}
}
}We read every tool's name, description and inputs the way the model will, looking for instructions hidden from you. A clean result means no warning signs, not a guarantee. Scanned Nov 3, 2026.
No readOnlyHint / destructiveHint annotations, so clients can't tell a read from a write without asking.
Fix: Add annotations to each tool, e.g. { readOnlyHint: true } for tools that only read.