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A2A Indirect Prompt-Injection & Jailbreak Firewall
A2A Indirect Prompt-Injection & Jailbreak Firewall is a paid API for AI agents from mcp-compiler.agentdiet.dev, paid per call via MPP, $0.005/call, status unknown (last checked 2026-10-21).
Scans untrusted text, HTML, emails, MCP responses, or A2A payloads for hidden prompt injections and jailbreak attempts, returning sanitized content.
Price / call$0.005
Success—
StatusUnknown
How this service works
Scans untrusted web pages, emails, MCP responses, or A2A payloads for hidden prompt injections and returns sanitized text. (Live x402 v2, IETF MPP & MCP endpoint at https://mcp-compiler.agentdiet.dev/v1/guard)
Output
Returns an object containing the scan result, indicating whether the input contains hidden prompt injection or jailbreak payloads, along with sanitized text safe for downstream LLM consumption.
Example use cases
Protect agent from malicious web content
“I'm about to feed this scraped web page into my agent pipeline — can you first scan it for any hidden prompt injections or jailbreak attempts embedded in the HTML before it touches the model?”
Sanitize inbound email before LLM processing
“I have an email from an unknown sender that my agent needs to summarize — please run it through the prompt injection firewall first to make sure there are no adversarial instructions hidden in the body.”
Guard MCP tool response before use
“My agent just got back a response from an external MCP tool and I want to make sure it's clean — can you scan it for any indirect prompt injection payloads or jailbreak content before we act on it?”
Technical details
Endpoint
GEThttps://mcp-compiler.agentdiet.dev/v1/guard?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your agent pipeline ingests text from untrusted external sources — web scrapes, emails, MCP tool responses, or A2A payloads — and you need a dedicated firewall layer to detect and strip indirect prompt injection or jailbreak attempts before the content reaches your LLM. It is purpose-built for A2A and MCP security contexts, making it more appropriate than general-purpose content filters when the threat model specifically involves adversarial prompt manipulation targeting AI agents.
Side effects
- Empty or missing 'text' parameter returns a validation error
- Extremely long inputs may be truncated or rejected
- False negatives: novel or obfuscated injection techniques may not be detected
- Service unavailable or payment required (HTTP 402) if micropayment not completed
- Ambiguous HTML encoding may cause inconsistent sanitization results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string | Untrusted text, HTML, or tool output to scan for hidden prompt injection or jailbreak payloads |
Output
Schema · Response
{
"type": "object"
}Reviews
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