dcl-trust-oracle

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as com.fronesislabs/dcl-trust-oracle and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 4 Oct 2026. Not supplied by the maker.

• dcl_evaluate_fast

  FAST Pre-Action Audit ($0.01). Runs the response through the server's "default" policy: a substring check against 3 forbidden phrases ("ignore previous instructions", "jailbreak", "bypass safety") wit

• dcl_evaluate_strict

  STRICT Pre-Action Audit ($0.05). Runs the response against a broader, higher-bar "strict" policy: the union of all forbidden phrases from the default, anti-jailbreak, and safety policies (8 phrases to

• dcl_evaluate_jailbreak

  PRE-ACTION Instruction Adherence Check ($0.02). Runs the "anti_jailbreak" policy: a substring check against 6 forbidden phrases ("ignore previous instructions", "jailbreak", "bypass safety", "pretend

• dcl_evaluate_safety

  PRE-ACTION Baseline Safety Check ($0.01). Runs the "safety" policy: flags 2 forbidden disclaimers ("I cannot be held responsible", "no guarantees") and additionally REQUIRES the substring "AI" to appe

• dcl_evaluate_quality

  PRE-ACTION Content Quality & Drift Check ($0.03). Runs the "content_quality" policy: flags 12 absolutist or unverifiable-claim phrases (e.g. "guaranteed returns", "100% accurate", "studies show", "wit

• dcl_evaluate_secrets

  POST-ACTION Secret & Credential Leak Scan ($0.02). Regex-based scan across 8 categories (API keys, cloud credentials, tokens/JWTs, private keys, DB URLs, connection strings, env assignments, webhook s

• dcl_evaluate_pii

  POST-ACTION PII Detection Scan ($0.02). Regex-based scan across 8 personal-data categories, with a Luhn checksum on card numbers to reduce false positives. Any finding results in NO_COMMIT.

• dcl_evaluate_batch

  PRE-ACTION Bulk Processing ($0.10). Evaluates a list of items in one call; each item is a dict shaped {"response": str, "policy"?: str}, where policy defaults to "default" if omitted and may be any bu

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