Deterministic AI-liability attribution: signed, Bitcoin-anchored vendor/deployer/user fault split.
Maintain this server? Claim it
Call this server's tools from your browser. Nothing to install.
Requests go through mcptry because browsers can't call most MCP servers directly. Header values are sent to the server for that request only and are never stored or logged.
Tool list from our last check. Connect live to refresh it.
Deterministic prospective-evaluation gate (FK-METHOD-2026-006). Pass a ProposedAction BEFORE the agent delivers a response; receive one of three verdicts: 'allow', 'require_revision' (with specific factor-keyed directives), or 'block'. Uses the same four-factor engine that issues post-hoc certificates, so a single incident chains: prospective_pre_image -> response -> certificate -> anchor. This is a policy gate on structured action metadata, NOT a content safety classifier on raw prose. Thresholds are per-jurisdiction (EU strictest, US most permissive); read via GET /api/v2/gate/thresholds. Overrides are allowed but REQUIRE a governance rationale so the audit trail is complete. Cost: 1 credit. Pure deterministic.
The structured ProposedAction to evaluate.
Optional per-call threshold override. Rationale REQUIRED for audit.
This tool isn't marked read-only, so it may change something on the server or in an account you connected.
Deterministic prospective-evaluation gate (FK-METHOD-2026-006). Pass a ProposedAction BEFORE the agent delivers a response; receive one of three verdicts: 'allow', 'require_revision' (with specific factor-keyed directives), or 'block'. Uses the same four-factor engine that issues post-hoc certificates, so a single incident chains: prospective_pre_image -> response -> certificate -> anchor. This is a policy gate on structured action metadata, NOT a content safety classifier on raw prose. Thresholds are per-jurisdiction (EU strictest, US most permissive); read via GET /api/v2/gate/thresholds. Overrides are allowed but REQUIRE a governance rationale so the audit trail is complete. Cost: 1 credit. Pure deterministic.
| Argument | Type | Description |
|---|---|---|
| action* | object | The structured ProposedAction to evaluate. |
| overrides | object | Optional per-call threshold override. Rationale REQUIRED for audit. |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"action"
],
"properties": {
"action": {
"type": "object",
"required": [
"action_id",
"action_type",
"acting_agent_id",
"acting_agent_type",
"severity_estimate"
],
"properties": {
"eu_flags": {
"type": "object",
"properties": {
"high_risk_ai": {
"type": "boolean"
},
"pld_compensable_damage": {
"type": "boolean"
},
"human_oversight_unassigned_or_unqualified": {
"type": "boolean"
}
},
"description": "Optional EU AI Act flags; only used when jurisdiction === 'EU'."
},
"action_id": {
"type": "string",
"description": "Stable id for this action; echoed back."
},
"action_type": {
"enum": [
"llm_response",
"tool_call",
"code_execution",
"external_api_call",
"human_handoff",
"data_modification",
"financial_transaction",
"medical_advice",
"legal_advice",
"financial_advice",
"content_moderation",
"autonomous_decision",
"other"
],
"type": "string",
"description": "The action category. Carries inherent regulatory weight."
},
"jurisdiction": {
"enum": [
"AU",
"EU",
"US",
"UK",
"CA"
],
"type": "string",
"description": "Jurisdiction overlay; defaults to AU."
},
"cascade_depth": {
"type": "integer",
"maximum": 9007199254740991,
"minimum": 0,
"description": "How many upstream agents this action is downstream of. 0 = root; 3 = LLM->agent->tool->this. Applies cascade attenuation."
},
"context_flags": {
"type": "object",
"properties": {
"regulated_domain": {
"type": "boolean"
},
"irreversible_if_executed": {
"type": "boolean"
},
"human_in_the_loop_present": {
"type": "boolean"
},
"affects_vulnerable_population": {
"type": "boolean"
}
},
"description": "Context flags that inform the regulatoryAlignment and controllability sub-scores."
},
"acting_agent_id": {
"type": "string",
"description": "Free-form id of the agent issuing the action."
},
"acting_agent_type": {
"enum": [
"ai_system",
"vendor",
"deployer",
"operator",
"human_user",
"third_party"
],
"type": "string",
"description": "Liability-bias category of the acting agent."
},
"severity_estimate": {
"enum": [
"low",
"medium",
"high",
"critical"
],
"type": "string",
"description": "The estimated severity if the action goes wrong."
},
"upstream_incident_id": {
"type": "string",
"description": "Optional chain to an existing incident trace."
}
},
"description": "The structured ProposedAction to evaluate."
},
"overrides": {
"type": "object",
"required": [
"rationale"
],
"properties": {
"rationale": {
"type": "string",
"description": "REQUIRED when overrides are provided. Cite the governance basis (e.g. 'ISO/IEC 42001 SoA §3.2 approval')."
},
"allow_below": {
"type": "number",
"maximum": 1,
"minimum": 0
},
"block_at_or_above": {
"type": "number",
"maximum": 1,
"minimum": 0
}
},
"description": "Optional per-call threshold override. Rationale REQUIRED for audit."
}
}
}Claude-powered structured extractor. Parses unstructured text (news articles, court filings, emails, PDFs, incident reports, logs) into the typed JSON schema required by submit_incident. Returns a ready-to-submit incident object with extracted agents, events, severity, jurisdiction, and financial impact. NOTE: This is a pre-processing convenience tool — the deterministic scoring engine itself remains LLM-free. Cost: 10 credits.
| Argument | Type | Description |
|---|---|---|
| text* | string | Unstructured text to extract from. Can be a news article, court filing, incident report, email, PDF text, log output, or any description of an AI incident. |
| context_hint | string | Optional hint about the source type (e.g., 'court filing', 'news article', 'internal incident report') to improve extraction accuracy. |
| jurisdiction_hint | string | Optional ISO country code hint if the jurisdiction is known (e.g., 'AU', 'US', 'EU'). |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"text"
],
"properties": {
"text": {
"type": "string",
"maxLength": 50000,
"minLength": 20,
"description": "Unstructured text to extract from. Can be a news article, court filing, incident report, email, PDF text, log output, or any description of an AI incident."
},
"context_hint": {
"type": "string",
"description": "Optional hint about the source type (e.g., 'court filing', 'news article', 'internal incident report') to improve extraction accuracy."
},
"jurisdiction_hint": {
"type": "string",
"description": "Optional ISO country code hint if the jurisdiction is known (e.g., 'AU', 'US', 'EU')."
}
}
}Return the index of all CausalLayer Tessera anchor batches, or one batch's full JSON (signed Merkle root, leaves, OpenTimestamps proof reference). FREE.
| Argument | Type | Description |
|---|---|---|
| version | string | Optional anchor version, e.g. '2026-05-16-v1.6.4-simulation-calibration'. |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"version": {
"type": "string",
"description": "Optional anchor version, e.g. '2026-05-16-v1.6.4-simulation-calibration'."
}
}
}Return the CausalLayer issuer registry, or one issuer record. The registry lists all trusted public-key fingerprints, key algorithms, validity windows, and the anchor-log repo for each active issuer. FREE — no API key required.
| Argument | Type | Description |
|---|---|---|
| issuer_id | string | Optional issuer id, e.g. 'causallayer-prod-2026-q2'. If omitted, returns the full registry. |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"issuer_id": {
"type": "string",
"description": "Optional issuer id, e.g. 'causallayer-prod-2026-q2'. If omitted, returns the full registry."
}
}
}Multi-jurisdiction overlay (FK-METHOD-2026-004). Given a canonical attributable apportionment (party-id -> share), the union of all jurisdiction role tags on each actor, and the union of jurisdiction-specific flags, return side-by-side post-overlay shares for AU, EU, US, UK, CA (or a chosen subset) with the specific rules that fired in each, citation URLs, and a parties × jurisdictions matrix. v1 ships full implementations for AU and EU; US/UK/CA are research stubs marked `is_stub: true`. Use GET /api/v2/jurisdiction/catalog to discover support and stub status. Cost: 1 credit. Pure deterministic.
| Argument | Type | Description |
|---|---|---|
| flags* | object | Union of jurisdiction-specific flags. AI Act / PLD flags drive the EU overlay; ACL / CPS 230 / VAISS flags drive the AU overlay. |
| actors* | array | All actors with the union of jurisdiction-specific role tags. EU and AU tags coexist on the same actor record. |
| attributable* | object | Canonical pre-overlay apportionment as { party_id: share }. Sum should approximate 1.0; the function renormalises within tolerance. |
| jurisdictions | array | Optional subset to compute. Defaults to all five. |
| primaryJurisdiction | string | Engine-level jurisdiction string (e.g. 'EU', 'DE', 'AU'). Used by the EU gate to decide engagement. |
Counterfactual remediation simulator. Given a certificate's verdict + fourFactorScoring + agents and a list of remediation IDs from the FK-METHOD-2026-003 catalog, return the apportioned shares each remediation would have produced (in isolation) and the composite shares if they all stack. Every remediation cites a specific statute or standard. GET /api/v2/remediation/catalog for the list of IDs. Cost: 1 credit (same price as verify_certificate). Pure deterministic; same inputs produce a byte-identical result.
| Argument | Type | Description |
|---|---|---|
| agents* | array | Agent registry (id + type) so the simulator can map remediation targetType to specific party ids. |
| verdict* | object | The verdict block from the CausalCertificate. |
| remediations* | array | List of remediation IDs from the catalog (e.g. vendor_adversarial_eval_suite, deployer_human_in_loop). Each may optionally pin appliedToParty to a specific agent id. |
| fourFactorScoring* | object | The fourFactorScoring block from the CausalCertificate. |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"verdict",
"fourFactorScoring",
"agents",
"remediations"
],
"properties": {
"agents": {
"type": "array",
"items": {
"type": "object",
"required": [
"id"
],
"properties": {
"id": {
"type": "string"
},
"type": {
"type": "string"
}
}
},
"description": "Agent registry (id + type) so the simulator can map remediation targetType to specific party ids."
},
"verdict": {
"type": "object",
"required": [
"primaryParty",
"primaryShare",
"secondary"
],
"properties": {
"secondary": {
"type": "array",
"items": {
"type": "object",
"required": [
"party",
"share"
],
"properties": {
"party": {
"type": "string"
},
"share": {
"type": "number",
"maximum": 1,
"minimum": 0
}
}
}
},
"primaryParty": {
"type": "string"
},
"primaryShare": {
"type": "number",
"maximum": 1,
"minimum": 0
}
},
"description": "The verdict block from the CausalCertificate."
},
"remediations": {
"type": "array",
"items": {
"type": "object",
"required": [
"id"
],
"properties": {
"id": {
"type": "string"
},
"appliedToParty": {
"type": "string"
}
}
},
"minItems": 1,
"description": "List of remediation IDs from the catalog (e.g. vendor_adversarial_eval_suite, deployer_human_in_loop). Each may optionally pin appliedToParty to a specific agent id."
},
"fourFactorScoring": {
"type": "object",
"required": [
"primaryAgent",
"causalProximity",
"behaviouralDeviation",
"controllability",
"regulatoryAlignment",
"weights"
],
"properties": {
"weights": {
"type": "object",
"required": [
"causalProximity",
"behaviouralDeviation",
"controllability",
"regulatoryAlignment"
],
"properties": {
"causalProximity": {
"type": "number"
},
"controllability": {
"type": "number"
},
"regulatoryAlignment": {
"type": "number"
},
"behaviouralDeviation": {
"type": "number"
}
}
},
"primaryAgent": {
"type": "string"
},
"causalProximity": {
"type": "number",
"maximum": 1,
"minimum": 0
},
"controllability": {
"type": "number",
"maximum": 1,
"minimum": 0
},
"regulatoryAlignment": {
"type": "number",
"maximum": 1,
"minimum": 0
},
"behaviouralDeviation": {
"type": "number",
"maximum": 1,
"minimum": 0
}
},
"description": "The fourFactorScoring block from the CausalCertificate."
}
}
}Submit an AI incident for deterministic causal liability attribution. Returns a signed CausalCertificate, per-agent liability allocation, evidence-chain completeness, regulatory mapping, and (where keys are configured) a Bitcoin-anchored proof. Cost: 50 credits. Three guardrails apply: PII scan, deterministic-only acknowledgement, and minimum evidence.
| Argument | Type | Description |
|---|---|---|
| title* | string | |
| agents* | array | |
| events* | array | |
| category | string | |
| currency | string | |
| severity | string | |
| description | string | |
| jurisdiction | string | |
| pii_acknowledged | boolean | G1: Set to true ONLY if caller has confirmed PII handling is permitted by their data agreement. False payloads with detected PII will be rejected. |
Convert an OpenTelemetry OTLP JSON trace into a FaultKey incident and return the same deterministic CausalCertificate as submit_incident. Each span becomes an event; service.name groups spans into agents; W3C trace_id and span_id propagate as evidence pointers on the causal graph edges. Cost: 50 credits (same as submit_incident). Three guardrails apply: PII scan, deterministic-only acknowledgement, and minimum evidence (auto-satisfied when the trace has at least 1 span).
| Argument | Type | Description |
|---|---|---|
| otlp* | object | OTLP JSON payload with resourceSpans[]. See https://opentelemetry.io/docs/specs/otlp/#json-protobuf-encoding |
| title* | string | |
| category | string | |
| currency | string | |
| jurisdiction | string | |
| pii_acknowledged | boolean | G1: Set to true ONLY if PII handling is permitted by your data agreement. OTLP traces frequently leak user/session ids in attributes. |
| deterministic_only* | boolean | G2: Must be true. Acknowledges CausalLayer is deterministic. |
| financial_impact_cents |
Independently verify a CausalCertificate end-to-end (signature, Merkle integrity, issuer status against the registry). Cost: 1 credit. In production env, certificates from non-active issuers are rejected.
| Argument | Type | Description |
|---|---|---|
| certificate* | object | CausalCertificateV1 object as returned by submit_incident.certificate |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"certificate"
],
"properties": {
"certificate": {
"type": "object",
"description": "CausalCertificateV1 object as returned by submit_incident.certificate",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
}
}
}Independently re-derive a CausalCertificate from its canonical input and compare byte-for-byte against the claimed certificate. This is the strongest verification path: it requires no trust in the issuer or signing key. Cost: 1 credit (same price as verify_certificate). Returns PASS only if every checked field (certificateId, request_hash, merkleRoot, verdict, causalGraph, fourFactorScoring, deviationTaxonomy, euRuleOverlay, cascadeAttenuation, damages, underwriting) matches identically.
| Argument | Type | Description |
|---|---|---|
| certificate* | object | The CausalCertificate object claimed by the issuer. |
| canonicalInput* | object | The original incident body that produced the certificate — the same JSON originally posted to submit_incident or submit_otel_trace. |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"certificate",
"canonicalInput"
],
"properties": {
"certificate": {
"type": "object",
"description": "The CausalCertificate object claimed by the issuer.",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
},
"canonicalInput": {
"type": "object",
"description": "The original incident body that produced the certificate — the same JSON originally posted to submit_incident or submit_otel_trace.",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
}
}
}{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"attributable",
"actors",
"flags"
],
"properties": {
"flags": {
"type": "object",
"properties": {
"high_risk_ai": {
"type": "boolean"
},
"vaiss_adherent": {
"type": "boolean"
},
"vendor_no_docs": {
"type": "boolean"
},
"acl_major_failure": {
"type": "boolean"
},
"ai_is_opaque_black_box": {
"type": "boolean"
},
"pld_compensable_damage": {
"type": "boolean"
},
"deployer_destroyed_logs": {
"type": "boolean"
},
"cps230_thirdparty_breach": {
"type": "boolean"
},
"cps230_operational_breach": {
"type": "boolean"
},
"is_apra_regulated_service": {
"type": "boolean"
},
"deployer_ignored_risk_signal": {
"type": "boolean"
},
"substantial_modification_present": {
"type": "boolean"
},
"defendant_failed_disclosure_order": {
"type": "boolean"
},
"provider_breach_was_unforeseeable": {
"type": "boolean"
},
"substantial_modification_severity": {
"type": "number",
"maximum": 1,
"minimum": 0
},
"deployer_employer_no_worker_notice": {
"type": "boolean"
},
"deployer_input_data_unrepresentative": {
"type": "boolean"
},
"deployer_public_authority_unregistered": {
"type": "boolean"
},
"deployer_used_contrary_to_instructions": {
"type": "boolean"
},
"provider_failed_to_supply_instructions": {
"type": "boolean"
},
"human_oversight_unassigned_or_unqualified": {
"type": "boolean"
},
"deployer_failed_serious_incident_notification": {
"type": "boolean"
},
"human_oversight_nominally_assigned_not_present": {
"type": "boolean"
}
},
"description": "Union of jurisdiction-specific flags. AI Act / PLD flags drive the EU overlay; ACL / CPS 230 / VAISS flags drive the AU overlay."
},
"actors": {
"type": "array",
"items": {
"type": "object",
"required": [
"id",
"type"
],
"properties": {
"id": {
"type": "string"
},
"type": {
"enum": [
"ai_system",
"vendor",
"deployer",
"human_operator",
"user",
"third_party"
],
"type": "string"
},
"eu_resident": {
"type": "boolean"
},
"acl_supplier": {
"type": "boolean"
},
"unrecoverable": {
"type": "boolean"
},
"apra_regulated": {
"type": "boolean"
},
"eu_chain_member": {
"type": "array",
"items": {
"enum": [
"manufacturer",
"authorised_representative",
"importer",
"fulfilment_service_provider",
"distributor",
"online_platform_self_supplier",
"substantial_modifier"
],
"type": "string"
}
}
}
},
"description": "All actors with the union of jurisdiction-specific role tags. EU and AU tags coexist on the same actor record."
},
"attributable": {
"type": "object",
"description": "Canonical pre-overlay apportionment as { party_id: share }. Sum should approximate 1.0; the function renormalises within tolerance.",
"propertyNames": {
"type": "string"
},
"additionalProperties": {
"type": "number",
"maximum": 1,
"minimum": 0
}
},
"jurisdictions": {
"type": "array",
"items": {
"enum": [
"AU",
"EU",
"US",
"UK",
"CA"
],
"type": "string"
},
"description": "Optional subset to compute. Defaults to all five."
},
"primaryJurisdiction": {
"type": "string",
"description": "Engine-level jurisdiction string (e.g. 'EU', 'DE', 'AU'). Used by the EU gate to decide engagement."
}
}
}| deterministic_only* |
| boolean |
| G2: Must be true. Acknowledges CausalLayer is deterministic and not LLM-based. |
| financial_impact_cents | any |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"title",
"agents",
"events",
"deterministic_only"
],
"properties": {
"title": {
"type": "string",
"minLength": 3
},
"agents": {
"type": "array",
"items": {
"type": "object",
"required": [
"id",
"name",
"type"
],
"properties": {
"id": {
"type": "string",
"minLength": 1
},
"name": {
"type": "string",
"minLength": 1
},
"type": {
"enum": [
"ai_system",
"human_operator",
"vendor",
"deployer",
"user",
"third_party"
],
"type": "string"
},
"model_id": {
"type": "string"
},
"vendor_name": {
"type": "string"
},
"operator_role": {
"enum": [
"provider",
"deployer",
"user",
"vendor",
"regulator",
"auditor"
],
"type": "string"
}
}
},
"minItems": 1
},
"events": {
"type": "array",
"items": {
"type": "object",
"required": [
"id",
"type",
"timestamp",
"description"
],
"properties": {
"id": {
"type": "string",
"minLength": 1
},
"type": {
"type": "string",
"minLength": 1
},
"span_id": {
"type": "string",
"pattern": "^[0-9a-f]{16}$"
},
"actor_id": {
"type": "string"
},
"trace_id": {
"type": "string",
"pattern": "^[0-9a-f]{32}$"
},
"timestamp": {
"type": "string",
"minLength": 1
},
"description": {
"type": "string",
"minLength": 1
},
"trace_source": {
"enum": [
"opentelemetry",
"jaeger",
"zipkin",
"datadog",
"newrelic",
"other"
],
"type": "string"
}
}
},
"minItems": 1
},
"category": {
"type": "string"
},
"currency": {
"type": "string",
"maxLength": 3,
"minLength": 3
},
"severity": {
"enum": [
"low",
"medium",
"high",
"critical"
],
"type": "string"
},
"description": {
"type": "string"
},
"jurisdiction": {
"type": "string"
},
"pii_acknowledged": {
"type": "boolean",
"default": false,
"description": "G1: Set to true ONLY if caller has confirmed PII handling is permitted by their data agreement. False payloads with detected PII will be rejected."
},
"deterministic_only": {
"type": "boolean",
"const": true,
"description": "G2: Must be true. Acknowledges CausalLayer is deterministic and not LLM-based."
},
"financial_impact_cents": {
"anyOf": [
{
"type": "integer",
"maximum": 9007199254740991,
"minimum": 0
},
{
"type": "null"
}
]
}
}
}| any |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"title",
"otlp",
"deterministic_only"
],
"properties": {
"otlp": {
"type": "object",
"description": "OTLP JSON payload with resourceSpans[]. See https://opentelemetry.io/docs/specs/otlp/#json-protobuf-encoding",
"propertyNames": {
"type": "string"
},
"additionalProperties": {}
},
"title": {
"type": "string",
"minLength": 3
},
"category": {
"type": "string"
},
"currency": {
"type": "string",
"maxLength": 3,
"minLength": 3
},
"jurisdiction": {
"type": "string"
},
"pii_acknowledged": {
"type": "boolean",
"default": false,
"description": "G1: Set to true ONLY if PII handling is permitted by your data agreement. OTLP traces frequently leak user/session ids in attributes."
},
"deterministic_only": {
"type": "boolean",
"const": true,
"description": "G2: Must be true. Acknowledges CausalLayer is deterministic."
},
"financial_impact_cents": {
"anyOf": [
{
"type": "integer",
"maximum": 9007199254740991,
"minimum": 0
},
{
"type": "null"
}
]
}
}
}