MCP 服务器
FlareSignal Intelligence
io.flaresignal/intelligence
此 MCP 可以做什么
Provides provenance-aware Flare and XRPFi intelligence through canonical metrics, analytical compositions, research plans and traceable agent workflows.
功能
工具
59
工具
flaresignal.agent.access.catalog
Agent access and delegation catalogue
Describe API-key bootstrap, short-lived delegated agent sessions, read-only scope profiles, TTL limits, live entitlement/revocation policy and the non-delegable generic-surface boundary.
只读
幂等
输入模式
{'type': 'object', 'properties': []}
输出模式
{'type': 'object'}
flaresignal.agent.brief.query
Broad Flare intelligence brief
Route a broad natural-language Flare question to a compact provenance-aware packet of entitled canonical observations with deterministic drill-down capabilities and follow-up questions.
只读
幂等
输入模式
{'type': 'object', 'properties': {'query': {'type': 'string', 'maxLength': 300}, 'packet': {'type': 'string'}, 'max_metrics': {'type': 'integer', 'maximum': 30, 'minimum': 1}}}
输出模式
{'type': 'object'}
flaresignal.agent.ontology.get
Flare economic ontology
Expose machine-only concepts, aliases and typed relationships connecting market, XRPFi, yield, collateral, productive capital, liquidity, value capture, events and historical coverage without asserting causality.
只读
幂等
输入模式
{'type': 'object', 'properties': {'concept': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.agent.plan
Plan deterministic agent research
Dry-run a evidence-backed research workflow over permanent cross-composition profiles. Returns declared claim/metric dependencies, execution order, propagated entitlements and current historical readiness without executing analytical compositions.
只读
幂等
输入模式
{'type': 'object', 'properties': {'asset': {'enum': ['FLR', 'SGB', 'XRP', 'FXRP'], 'type': 'string'}, 'query': {'type': 'string', 'maxLength': 400, 'minLength': 2}, 'range': {'enum': ['1D', '3D', '7D', '15D', '30D', '90D', '1Y', 'ALL'], 'type': 'string'}, 'event_id': {'type': 'integer', 'minimum': 1}, 'profile_id': {'enum': ['flr_structural_regime', 'flr_sgb_market_structure_regime', 'xrpfi_system_regime'], 'type': 'string'}, 'event_horizon': {'enum': ['1D', '7D', '30D', '90D'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.agent.questions.catalog
Agent question catalogue
Browse machine-only common questions and deterministic routes for broad Flare, XRPFi, yield, collateral, market-structure, risk and historical-research intents.
只读
幂等
输入模式
{'type': 'object', 'properties': {'topic': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.agent.research
Execute deterministic agent research
Execute a read-only research plan through the permanent cross-composition engine and return claim-level findings, contradictions, evidence gaps, selected evidence scope and reproducible lineage without re-deriving source metrics.
只读
幂等
输入模式
{'type': 'object', 'properties': {'asset': {'enum': ['FLR', 'SGB', 'XRP', 'FXRP'], 'type': 'string'}, 'query': {'type': 'string', 'maxLength': 400, 'minLength': 2}, 'range': {'enum': ['1D', '3D', '7D', '15D', '30D', '90D', '1Y', 'ALL'], 'type': 'string'}, 'event_id': {'type': 'integer', 'minimum': 1}, 'profile_id': {'enum': ['flr_structural_regime', 'flr_sgb_market_structure_regime', 'xrpfi_system_regime'], 'type': 'string'}, 'event_horizon': {'enum': ['1D', '7D', '30D', '90D'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.agent.research.trace
Trace one agent research packet
Return cached read-only lineage for one recent research packet: finding to domain to permanent composition to claim to canonical metric, dataset and source evidence.
只读
幂等
输入模式
{'type': 'object', 'required': ['research_id'], 'properties': {'research_id': {'type': 'string', 'pattern': '^fsrsh_[a-f0-9]{24}$'}}}
输出模式
{'type': 'object'}
flaresignal.agent.session.create
Create delegated agent session
Create a short-lived read-only agent session rooted in an existing FlareSignal API key. Requested scopes may only narrow the parent account authority.
只读
幂等
输入模式
{'type': 'object', 'properties': {'label': {'type': 'string', 'maxLength': 80}, 'scopes': {'oneOf': [{'type': 'string'}, {'type': 'array', 'items': {'type': 'string', 'pattern': '^flaresignal\\.[a-z0-9._-]+$'}}], 'description': 'Optional permanent capability IDs. Supply a comma-separated string or JSON array. Every requested capability must be delegable and currently entitled.'}, 'ttl_seconds': {'type': 'integer', 'maximum': 3600, 'minimum': 300}, 'scope_profile': {'enum': ['research_read', 'all_entitled_read'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.agent.session.get
Inspect delegated agent session
Inspect the current short-lived delegated agent session, its exact capability allow-list, expiry and live parent entitlement state without revealing the session secret.
只读
幂等
输入模式
{'type': 'object', 'properties': []}
输出模式
{'type': 'object'}
flaresignal.agent.task.contract
Agent task contract
Describe the deterministic task envelope, acceptance policy, state model, idempotency, session binding, result retention and A2A-adapter readiness without claiming native A2A protocol conformance.
只读
幂等
输入模式
{'type': 'object', 'properties': []}
输出模式
{'type': 'object'}
flaresignal.agent.task.get
Get deterministic agent task
Retrieve one recent session-bound task packet, acceptance decision, state history and result without re-executing the research.
只读
幂等
输入模式
{'type': 'object', 'required': ['task_id'], 'properties': {'task_id': {'type': 'string', 'pattern': '^fstask_[a-f0-9]{24}$'}}}
输出模式
{'type': 'object'}
flaresignal.agent.task.submit
Submit deterministic research task
Submit one session-bound read-only research task. FlareSignal preflights deterministic profile, delegated scope, live entitlement and historical readiness, then executes only the existing research stack when accepted.
只读
幂等
输入模式
{'type': 'object', 'properties': {'asset': {'enum': ['FLR', 'SGB', 'XRP', 'FXRP'], 'type': 'string'}, 'query': {'type': 'string', 'maxLength': 400, 'minLength': 2}, 'range': {'enum': ['1D', '3D', '7D', '15D', '30D', '90D', '1Y', 'ALL'], 'type': 'string'}, 'event_id': {'type': 'integer', 'minimum': 1}, 'task_type': {'enum': ['research'], 'type': 'string'}, 'profile_id': {'enum': ['flr_structural_regime', 'flr_sgb_market_structure_regime', 'xrpfi_system_regime'], 'type': 'string'}, 'event_horizon': {'enum': ['1D', '7D', '30D', '90D'], 'type': 'string'}, 'client_task_id': {'type': 'string', 'maxLength': 128}, 'idempotency_key': {'type': 'string', 'maxLength': 128, 'minLength': 8}}}
输出模式
{'type': 'object'}
flaresignal.agent.task.trace
Trace deterministic agent task
Trace a recent task from delegated task envelope through research and selected evidence lineage. The trace never broadens the underlying research evidence scope.
只读
幂等
输入模式
{'type': 'object', 'required': ['task_id'], 'properties': {'task_id': {'type': 'string', 'pattern': '^fstask_[a-f0-9]{24}$'}}}
输出模式
{'type': 'object'}
flaresignal.analytics.catalog
Analytical capability catalogue
List higher-level FlareSignal analytical capabilities that operate above raw data surfaces and declare their evidence, confidence and historical-completeness contract.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'domain': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.analytics.metric.context
Metric analytical context
Return an evidence-aware analytical packet for one canonical metric: latest observation, deterministic retained-range statistics, source context, requested-window readiness and explicit historical-completeness constraints without interpolation or prediction.
只读
幂等
输入模式
{'type': 'object', 'required': ['metric_key'], 'properties': {'range': {'enum': ['1D', '3D', '7D', '15D', '30D', '90D', '1Y', 'ALL'], 'type': 'string'}, 'max_points': {'type': 'integer', 'maximum': 1000, 'minimum': 12}, 'metric_key': {'type': 'string', 'maxLength': 160, 'minLength': 2}, 'include_series': {'type': 'boolean'}}}
输出模式
{'type': 'object'}
flaresignal.composed.catalog
Composed Intelligence catalogue
List deterministic multi-dataset analytical compositions, their declared canonical component metrics, input mode, supported ranges/event horizons, claim IDs and truth boundaries.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.composed.query
Run Composed Intelligence query
Assemble canonical FlareSignal metrics or permanent Event Intelligence checkpoints into evidence-linked conclusion objects with claim-level confidence, actual retained-window coverage and coverage-gated claim voting. Supports nine permanent compositions plus deterministic natural-language routing.
只读
幂等
输入模式
{'type': 'object', 'properties': {'query': {'type': 'string', 'maxLength': 400, 'minLength': 2}, 'range': {'enum': ['1D', '3D', '7D', '15D', '30D', '90D', '1Y', 'ALL'], 'type': 'string'}, 'event_id': {'type': 'integer', 'minimum': 1, 'description': 'Required when composition_id=event_before_after.'}, 'composition_id': {'enum': ['flr_structural_support', 'flr_sgb_structural_demand_compare', 'xrpfi_productive_capital_health', 'demand_structure_persistence', 'productive_scarcity', 'liquidity_regime', 'protocol_capital_flows', 'governance_policy_transmission', 'event_before_after'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.composed.synthesis.catalog
Cross-composition synthesis catalogue
List permanent cross-composition profiles, their child composition/claim dependencies, voting domains and truth boundaries.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.composed.synthesis.query
Run cross-composition synthesis
Reuse permanent composition packets to produce transparent cross-domain regime labels with visible domain postures, child claim lineage, no hidden score and optional non-voting Event Intelligence context.
只读
幂等
输入模式
{'type': 'object', 'properties': {'query': {'type': 'string', 'maxLength': 400, 'minLength': 2}, 'range': {'enum': ['1D', '3D', '7D', '15D', '30D', '90D', '1Y', 'ALL'], 'type': 'string'}, 'event_id': {'type': 'integer', 'minimum': 1}, 'profile_id': {'enum': ['flr_structural_regime', 'flr_sgb_market_structure_regime', 'xrpfi_system_regime'], 'type': 'string'}, 'event_horizon': {'enum': ['1D', '7D', '30D', '90D'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.a2a.get
Get native A2A adapter contract
Describe the native A2A 0.3 HTTP+JSON interface, supported operations, delegated-session authentication, polling task lifecycle and the exact boundary between A2A transport and the existing FlareSignal task/research engine.
只读
幂等
输入模式
{'type': 'object', 'properties': []}
输出模式
{'type': 'object'}
flaresignal.discovery.capabilities.get
Get machine capability
Resolve one canonical FlareSignal machine capability definition by permanent capability ID.
只读
幂等
输入模式
{'type': 'object', 'required': ['capability_id'], 'properties': {'capability_id': {'type': 'string', 'pattern': '^flaresignal\\.[a-z0-9._-]+$'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.capabilities.list
List machine capabilities
Enumerate the canonical FlareSignal machine capability registry with stable IDs, truth boundaries, access modes and discovery metadata.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'tag': {'type': 'string'}, 'state': {'type': 'string'}, 'access': {'type': 'string'}, 'domain': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.catalog
Browse agent discovery catalogue
Browse capability semantics designed for autonomous agents: assets, domains, intents, example questions, truth boundaries, access policy and invocation metadata.
只读
幂等
输入模式
{'type': 'object', 'properties': {'asset': {'type': 'string'}, 'topic': {'type': 'string'}, 'access': {'type': 'string'}, 'domain': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.datasets.get
Get canonical machine dataset
Resolve one permanent FlareSignal machine dataset contract by dataset ID.
只读
幂等
输入模式
{'type': 'object', 'required': ['dataset_id'], 'properties': {'dataset_id': {'type': 'string', 'pattern': '^flaresignal\\.dataset\\.[a-z0-9._-]+$'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.datasets.list
List canonical machine datasets
Enumerate permanent machine dataset IDs for every active canonical metric and canonical historical data family, including schemas, methodology, access and evidence-coverage state.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'kind': {'type': 'string'}, 'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 2000, 'minimum': 1}, 'state': {'type': 'string'}, 'offset': {'type': 'integer', 'minimum': 0}, 'network': {'type': 'string'}, 'category': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.distribution.get
Get agent distribution manifests
Return FlareSignal machine-distribution identity and publication artefacts for MCP Registry, x402 Bazaar and llms.txt without claiming third-party publication or indexing.
只读
幂等
输入模式
{'type': 'object', 'properties': {'format': {'enum': ['summary', 'mcp_registry', 'bazaar', 'llms'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.inventory.query
Query machine inventory
Inspect the current canonical metric, source and Intelligence module inventory without scraping presentation-layer pages.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 1000, 'minimum': 1}, 'offset': {'type': 'integer', 'minimum': 0}, 'include': {'enum': ['summary', 'metrics', 'sources', 'modules', 'datasets', 'surfaces', 'parity', 'all'], 'type': 'string'}, 'network': {'type': 'string'}, 'category': {'type': 'string'}, 'authority': {'type': 'string'}, 'source_type': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.metrics.catalog
Browse complete metric catalogue
Browse every active canonical FlareSignal metric definition with question examples, methodology/accounting metadata and direct machine invocation hints.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 250, 'minimum': 1}, 'offset': {'type': 'integer', 'minimum': 0}, 'network': {'type': 'string'}, 'category': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.metrics.search
Search registered metrics and answerable questions
Deterministically search the complete active FlareSignal metric registry by natural-language question, asset, domain or concept and return exact metric keys plus safe live/history invocation routes.
只读
幂等
输入模式
{'type': 'object', 'required': ['query'], 'properties': {'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 20, 'minimum': 1}, 'query': {'type': 'string', 'maxLength': 240, 'minLength': 2}, 'network': {'type': 'string'}, 'category': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.parity.get
Get machine parity audit
Audit every registered FlareSignal GET/read surface against the machine surface registry and report any human-data route without a structured machine equivalent.
只读
幂等
输入模式
{'type': 'object'}
输出模式
{'type': 'object'}
flaresignal.discovery.search
Search FlareSignal capabilities
Deterministically rank FlareSignal capabilities for a natural-language data question using curated capability semantics and synonyms; no LLM is used and the search does not answer the underlying intelligence question.
只读
幂等
输入模式
{'type': 'object', 'required': ['query'], 'properties': {'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 10, 'minimum': 1}, 'query': {'type': 'string', 'maxLength': 240, 'minLength': 2}, 'access': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.surfaces.get
Get structured surface contract
Resolve one FlareSignal human-product read surface contract, including its source route, machine route, input schema and original permission boundary.
只读
幂等
输入模式
{'type': 'object', 'required': ['surface_id'], 'properties': {'surface_id': {'type': 'string', 'pattern': '^flaresignal\\.surface\\.[a-z0-9._-]+$'}}}
输出模式
{'type': 'object'}
flaresignal.discovery.surfaces.list
List structured human-to-machine surfaces
Enumerate every structured GET surface used by the FlareSignal product with a permanent surface ID, schema and permission-preserving machine equivalent.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'kind': {'type': 'string'}, 'access': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.events.archive.query
Permanent Event Intelligence archive
Query the permanent classified Event Intelligence archive with provenance and outcome-state references through the common machine envelope.
只读
幂等
输入模式
{'type': 'object', 'properties': {'to': {'type': 'string'}, 'from': {'type': 'string'}, 'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 500, 'minimum': 1}, 'network': {'type': 'string'}, 'category': {'type': 'string'}, 'protocol': {'type': 'string'}, 'min_severity': {'type': 'integer', 'maximum': 5, 'minimum': 1}}}
输出模式
{'type': 'object'}
flaresignal.events.live.query
Live intelligence events
Query significance-ranked current FlareSignal events from the canonical live-event ledger. Returned event direction, actor and protocol context are evidence-backed and are not reconstructed by the machine layer.
只读
幂等
输入模式
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'maximum': 80, 'minimum': 1}, 'after_id': {'type': 'integer', 'minimum': 0}, 'category': {'type': 'string'}, 'protocol': {'type': 'string'}, 'before_id': {'type': 'integer', 'minimum': 0}, 'min_severity': {'type': 'integer', 'maximum': 5, 'minimum': 1}}}
输出模式
{'type': 'object'}
flaresignal.flow_atlas.stream
Canonical Flow Atlas stream
Query the structured Flow Atlas composite stream used by the live visual: verified market executions, evidence-backed live events, verified wallet transfers and explicitly labelled measured state changes. The machine layer does not infer geography, trade side or protocol transfers beyond the stored evidence.
只读
幂等
输入模式
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'maximum': 160, 'minimum': 10}, 'after_event': {'type': 'integer', 'minimum': 0}, 'after_trade': {'type': 'integer', 'minimum': 0}, 'after_transfer': {'type': 'integer', 'minimum': 0}}}
输出模式
{'type': 'object'}
flaresignal.history.availability.query
Historical packet availability map
Expose verified monthly historical availability with canonical dataset identity plus canonical metric-history coverage so agents can assess what evidence is available before requesting a research packet.
只读
幂等
输入模式
{'type': 'object'}
输出模式
{'type': 'object'}
flaresignal.history.coverage.query
Historical metric coverage map
Query retained metric history and, on request, canonical dataset readiness with alias resolution, earliest/latest evidence bounds, completeness where defensible, explicit gaps and source-bounded semantics.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 250, 'minimum': 1}, 'state': {'type': 'string'}, 'offset': {'type': 'integer', 'minimum': 0}, 'dataset': {'type': 'string'}, 'network': {'type': 'string'}, 'category': {'type': 'string'}, 'dataset_q': {'type': 'string'}, 'dataset_state': {'type': 'string'}, 'include_datasets': {'type': 'boolean'}}}
输出模式
{'type': 'object'}
flaresignal.history.intelligence.query
Advanced historical intelligence
Classify canonical dataset history by coverage quality, explicit gap type, provenance strength, deterministic evidence confidence, completeness and safe-use decision support. Optionally includes cadence-based expected-vs-observed metric gap reasoning without manufacturing missing observations.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 100, 'minimum': 1}, 'state': {'type': 'string'}, 'offset': {'type': 'integer', 'minimum': 0}, 'dataset': {'type': 'string'}, 'network': {'type': 'string'}, 'quality': {'type': 'string'}, 'category': {'type': 'string'}, 'gap_class': {'type': 'string'}, 'metric_limit': {'type': 'integer', 'maximum': 100, 'minimum': 1}, 'include_metrics': {'type': 'boolean'}}}
输出模式
{'type': 'object'}
flaresignal.intelligence.catalog.get
Intelligence capability catalogue
Discover the current FlareSignal Intelligence modules, sections, access boundaries and readiness state as structured metadata rather than scraping the navigation or rendered page HTML.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'category': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.market.executions.latest
Verified market execution tape
Query retained verified/derived FLR and SGB exchange executions used by Flow Atlas. Venue-reported side is preserved and never inferred when absent.
只读
幂等
输入模式
{'type': 'object', 'properties': {'after': {'type': 'integer', 'minimum': 0}, 'asset': {'enum': ['FLR', 'SGB', 'BOTH'], 'type': 'string', 'default': 'BOTH'}, 'limit': {'type': 'integer', 'maximum': 80, 'minimum': 10}}}
输出模式
{'type': 'object'}
flaresignal.market.history.query
Market chart history
Query canonical FTSO price history joined to the configured reference-venue volume evidence through the common machine envelope. Empty intervals remain empty and no price interpolation is manufactured.
只读
幂等
输入模式
{'type': 'object', 'required': ['asset'], 'properties': {'asset': {'enum': ['FLR', 'SGB'], 'type': 'string'}, 'hours': {'type': 'integer', 'maximum': 8760, 'minimum': 0}}}
输出模式
{'type': 'object'}
flaresignal.market.truth.live
Current canonical market truth
Return the current official FTSO-led FLR/SGB/XRP market truth through the common FlareSignal machine envelope, including source health, evidence timestamps and exact 24-hour voting-round change context.
只读
幂等
输入模式
{'type': 'object', 'properties': {'keys': {'type': 'string', 'description': 'Optional comma-separated metric keys to include alongside the canonical price packet.'}}}
输出模式
{'type': 'object'}
flaresignal.metrics.history.query
Canonical metric history
Query retained canonical observations for one registered FlareSignal metric through the common machine envelope. Entitlement and public/Pro history-depth boundaries remain identical to the human site.
只读
幂等
输入模式
{'type': 'object', 'required': ['key'], 'properties': {'key': {'type': 'string', 'pattern': '^[a-z0-9._-]+$'}, 'hours': {'type': 'integer', 'maximum': 8760, 'minimum': 0}, 'limit': {'type': 'integer', 'maximum': 2000, 'minimum': 1}}}
输出模式
{'type': 'object'}
flaresignal.metrics.live.query
Current live metric packet
Query current registered FlareSignal metric observations through the common machine envelope. Each metric remains governed by its own entitlement, methodology, source timestamp and freshness state.
只读
幂等
输入模式
{'type': 'object', 'required': ['keys'], 'properties': {'keys': {'type': 'string', 'description': 'Comma-separated canonical metric keys, maximum 80.'}}}
输出模式
{'type': 'object'}
flaresignal.opportunities.catalog
Browse Yield & Capital Opportunity catalogue
Browse evidence-backed XRPFi, FXRP/stXRP yield, native FLR/SGB staking/delegation and collateral opportunity profiles without ranking by return.
只读
幂等
输入模式
{'type': 'object', 'properties': {'asset': {'type': 'string'}, 'status': {'type': 'string'}, 'protocol': {'type': 'string'}, 'objective': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.opportunities.gaps
Get Yield & Capital evidence gaps
Return explicit evidence gaps that prevent FlareSignal from safely quoting comparable yield, deployable capacity or FLR/SGB collateral earnings for selected protocols and native-capital routes.
只读
幂等
输入模式
{'type': 'object'}
输出模式
{'type': 'object'}
flaresignal.opportunities.metric_map
Map all metrics to commercial questions
Classify every active canonical FlareSignal metric by Yield & Capital opportunity relevance, theme and question role while leaving the metric definition and entitlement unchanged.
只读
幂等
输入模式
{'type': 'object', 'properties': {'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 250, 'minimum': 1}, 'theme': {'type': 'string'}, 'offset': {'type': 'integer', 'minimum': 0}, 'category': {'type': 'string'}, 'relevance': {'enum': ['direct', 'supporting', 'context'], 'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.opportunities.scenario
Model current-rate Yield & Capital scenario
Model a stated amount and horizon only where an explicit current canonical APR/APY/fee metric exists; preserve underlying entitlements and report capacity/gaps without making a recommendation or forecast.
只读
幂等
输入模式
{'type': 'object', 'required': ['amount'], 'properties': {'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 10, 'minimum': 1}, 'amount': {'type': 'number', 'exclusiveMinimum': 0}, 'horizon_days': {'type': 'integer', 'maximum': 3650, 'minimum': 1}, 'opportunity_id': {'type': 'string', 'pattern': '^[a-z0-9._-]+$'}}}
输出模式
{'type': 'object'}
flaresignal.opportunities.search
Search Yield & Capital opportunities
Deterministically route a natural-language capital, yield, FXRP, staking, delegation or collateral question to the relevant FlareSignal opportunity profiles and underlying metrics.
只读
幂等
输入模式
{'type': 'object', 'required': ['query'], 'properties': {'asset': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 15, 'minimum': 1}, 'query': {'type': 'string', 'maxLength': 240, 'minLength': 2}}}
输出模式
{'type': 'object'}
flaresignal.payment.x402.canary
x402 settlement canary
Non-intelligence paid canary used only to prove FlareSignal x402 challenge, client signature, facilitator verification, post-handler settlement, receipt, replay protection, metering and audit linkage for isolated settlement verification.
只读
幂等
输入模式
{'type': 'object'}
输出模式
{'type': 'object'}
flaresignal.products.catalog
Browse machine intelligence products
Browse FlareSignal packaged intelligence products, request/response contract, billing unit, packet sections, truth boundaries and current execution state.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'asset': {'type': 'string'}, 'domain': {'type': 'string'}, 'time_scope': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.products.commercial
Get agent product commercial contract
Return the current quota, meter-unit, replay and execution-state contract for every executable intelligence packet, including whether monetary pricing or x402 settlement is enabled.
只读
幂等
输入模式
{'type': 'object'}
输出模式
{'type': 'object'}
flaresignal.products.execute
Execute authenticated agent intelligence product
Assemble one declared FlareSignal intelligence product from retained canonical evidence under a delegated-session quota and durable idempotent metering contract. No money is charged and x402 is not invoked.
只读
幂等
输入模式
{'type': 'object', 'required': ['product_id', 'idempotency_key'], 'properties': {'parameters': {'type': 'object'}, 'product_id': {'type': 'string', 'pattern': '^flaresignal\\.product\\.[a-z0-9._-]+$'}, 'idempotency_key': {'type': 'string', 'maxLength': 128, 'minLength': 8}}}
输出模式
{'type': 'object'}
flaresignal.products.search
Search intelligence products
Deterministically route a natural-language research or data-packaging need to the most relevant FlareSignal intelligence product contract.
只读
幂等
输入模式
{'type': 'object', 'required': ['query'], 'properties': {'limit': {'type': 'integer', 'maximum': 12, 'minimum': 1}, 'query': {'type': 'string', 'maxLength': 300, 'minLength': 2}}}
输出模式
{'type': 'object'}
flaresignal.products.spec
Get intelligence product specification
Return one exact FlareSignal product contract including request schema, packet sections, current execution state and truth boundary.
只读
幂等
输入模式
{'type': 'object', 'required': ['product_id'], 'properties': {'product_id': {'type': 'string', 'pattern': '^flaresignal\\.product\\.[a-z0-9._-]+$'}}}
输出模式
{'type': 'object'}
flaresignal.products.usage
Get authenticated agent product usage
Return the current parent-account UTC-day packet-unit quota, consumption and recent durable product executions for the presenting delegated agent session.
只读
幂等
输入模式
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'maximum': 100, 'minimum': 1}}}
输出模式
{'type': 'object'}
flaresignal.sources.health.query
Canonical source health
Query FlareSignal registered source identities and their current health/freshness evidence without scraping Production Runtime or presentation pages.
只读
幂等
输入模式
{'type': 'object', 'properties': {'q': {'type': 'string'}, 'limit': {'type': 'integer', 'maximum': 250, 'minimum': 1}, 'state': {'type': 'string'}, 'offset': {'type': 'integer', 'minimum': 0}, 'authority': {'type': 'string'}, 'source_type': {'type': 'string'}}}
输出模式
{'type': 'object'}
flaresignal.surface.invoke
Invoke structured product data surface
Invoke any registered FlareSignal human-product GET surface through the common machine envelope while preserving the exact original permission and entitlement boundary and reusing the same server callback without HTTP loopback.
只读
幂等
输入模式
{'type': 'object', 'required': ['surface_id'], 'properties': {'params': {'type': 'object', 'additionalProperties': True}, 'surface_id': {'type': 'string', 'pattern': '^flaresignal\\.surface\\.[a-z0-9._-]+$'}}}
输出模式
{'type': 'object'}
历史
近期工具变更
已添加
flaresignal.surface.invoke
2026年9月17日 12:40
已添加
flaresignal.sources.health.query
2026年9月17日 12:40
已添加
flaresignal.products.usage
2026年9月17日 12:40
已添加
flaresignal.products.spec
2026年9月17日 12:40
已添加
flaresignal.products.search
2026年9月17日 12:40
已添加
flaresignal.products.execute
2026年9月17日 12:40
已添加
flaresignal.products.commercial
2026年9月17日 12:40
已添加
flaresignal.products.catalog
2026年9月17日 12:40
已添加
flaresignal.payment.x402.canary
2026年9月17日 12:40
已添加
flaresignal.opportunities.search
2026年9月17日 12:40
已添加
flaresignal.opportunities.scenario
2026年9月17日 12:40
已添加
flaresignal.opportunities.metric_map
2026年9月17日 12:40
已添加
flaresignal.opportunities.gaps
2026年9月17日 12:40
已添加
flaresignal.opportunities.catalog
2026年9月17日 12:40
已添加
flaresignal.metrics.live.query
2026年9月17日 12:40
已添加
flaresignal.metrics.history.query
2026年9月17日 12:40
已添加
flaresignal.market.truth.live
2026年9月17日 12:40
已添加
flaresignal.market.history.query
2026年9月17日 12:40
已添加
flaresignal.market.executions.latest
2026年9月17日 12:40
已添加
flaresignal.intelligence.catalog.get
2026年9月17日 12:40
已添加
flaresignal.history.intelligence.query
2026年9月17日 12:40
已添加
flaresignal.history.coverage.query
2026年9月17日 12:40
已添加
flaresignal.history.availability.query
2026年9月17日 12:40
已添加
flaresignal.flow_atlas.stream
2026年9月17日 12:40
已添加
flaresignal.events.live.query
2026年9月17日 12:40
已添加
flaresignal.events.archive.query
2026年9月17日 12:40
已添加
flaresignal.discovery.surfaces.list
2026年9月17日 12:40
已添加
flaresignal.discovery.surfaces.get
2026年9月17日 12:40
已添加
flaresignal.discovery.search
2026年9月17日 12:40
已添加
flaresignal.discovery.parity.get
2026年9月17日 12:40
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