VIGO — The First MCP Server for Financial Regulatory Intelligence

Regulatory Intelligence Expert · Bilingual AI Agent for Hong Kong SFC Regulations

By OrphicOne · English & 繁體中文 · Continuously Updated Knowledge Base

What is VIGO?

VIGO (遠見 · 洞察 · 治理 · 優化) is a specialized financial regulatory intelligence AI agent — and the industry's first MCP server dedicated to financial regulatory intelligence in any jurisdiction.

At its core, VIGO is a regulatory intelligence expert: deeply versed in Hong Kong SFC regulations, enforcement history, licensing requirements, and AML/CFT rules. But VIGO is more than a compliance encyclopedia. It is a business-aware compliance navigator — an AI that understands how compliance intersects with business strategy, capital structures, and market reality.

Compliance is the floor. Business is the ceiling. VIGO helps you build both.

V.I.G.O. — The Four Dimensions

	Dimension	中文	Capability
V	Visionary	遠見	Capital path planning — IPO structures (18A/18C, SPAC), market positioning
I	Insight	洞察	Architecture design — Red-chip, VIE, LPF, OFC, SPC structures
G	Governance	治理	Regulatory mastery — SFC licensing (Type 1-13), FRR, AML/CTF
O	Optimization	優化	Cost-effective solutions — market pricing, talent policy, ROI

Why VIGO instead of asking Claude/ChatGPT directly?

	General AI	VIGO
Data	Frozen at training cutoff	Continuously updated — daily SFC sync + weekly HKMA/HKEX + monthly industry scan
Accuracy	Approximate, details often wrong	Precise — based on original regulatory documents with three-tier verification
Sources	None	Every answer includes official SFC document links with authority scores
Depth	Overview-level	Exam papers, exemptions, capital rules, enforcement details, fee benchmarks
Enforcement	Almost none	Searchable fines, bans, suspensions — 28 structured enforcement records
Perspective	Generic	Connects compliance requirements to business value (Iceberg Strategy)
Quality	No quality signals	Three-tier verification: GOLD (65%) / SILVER (35%) — World-Class metrics
Chinese	Generic translation	Professional regulatory terminology (繁體中文)
Intelligence	Static	Dual-model routing, 9-type query classification, self-correction engine

Asking ChatGPT about SFC regulations is like asking a smart friend — they roughly know. Asking VIGO is like consulting a senior compliance partner who knows every circular, every enforcement action, every licensing nuance, and always connects compliance back to your business objectives.

Quick Start

Claude (Web, Desktop, Mobile)

Settings → Connectors → Add custom connector → paste:

https://lsoatzzwpltpydwyfqqv.supabase.co/functions/v1/vigo-mcp

Claude will automatically invoke VIGO when you ask SFC compliance questions.

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "vigo": {
      "type": "streamableHttp",
      "url": "https://lsoatzzwpltpydwyfqqv.supabase.co/functions/v1/vigo-mcp"
    }
  }
}

VS Code

Add to .vscode/mcp.json:

{
  "servers": {
    "vigo": {
      "type": "streamableHttp",
      "url": "https://lsoatzzwpltpydwyfqqv.supabase.co/functions/v1/vigo-mcp"
    }
  }
}

Claude Code

claude mcp add --transport http vigo https://lsoatzzwpltpydwyfqqv.supabase.co/functions/v1/vigo-mcp

ChatGPT Desktop

{
  "mcpServers": {
    "vigo": {
      "url": "https://lsoatzzwpltpydwyfqqv.supabase.co/functions/v1/vigo-mcp"
    }
  }
}

Tools

VIGO provides 6 tools (4 read-only query tools + 2 analytical tools):

`query_regulation`

Ask any question about SFC regulations. Covers all license types, VATP/ASPIRe framework, AML/CFT, exams, CPD/CPT, and more. Bilingual — responds in whatever language you ask.

Parameter	Required	Description
`question`	Yes	Your regulatory question
`language`	No	`"en"`, `"zh"`, or `"auto"` (default)
`license_type`	No	Filter: `"Type 1"` through `"Type 13"`

`search_enforcement`

Search SFC enforcement actions — fines, suspensions, bans, and prosecutions.

Parameter	Required	Description
`query`	Yes	Company name, person, or violation type
`year`	No	Filter by year (e.g. `2025`)

`get_license_guide`

Comprehensive guide for any SFC license type: exams, capital, fit-and-proper, CPD.

Parameter	Required	Description
`license_type`	Yes	`"Type 1"` through `"Type 13"`
`aspect`	No	`"overview"`, `"exam"`, `"capital"`, `"fit_and_proper"`

`latest_updates`

Latest SFC regulatory updates: circulars, enforcement, VATP developments, consultations.

Parameter	Required	Description
`category`	No	`"circular"`, `"enforcement"`, `"vatp"`, `"consultation"`, `"all"`
`count`	No	Number of results, 1–10 (default: 5)

`compliance_check`

Perform a compliance health check for a licensed corporation. Input company profile, get a multi-dimensional compliance risk assessment.

Parameter	Required	Description
`license_types`	Yes	License types held, e.g. `["Type 1", "Type 9"]`
`num_ros`	No	Number of Responsible Officers
`num_staff`	No	Total number of staff
`aum`	No	Assets under management, e.g. `"500M HKD"`
`business_areas`	No	Business areas, e.g. `["securities dealing", "asset management"]`
`has_vatp`	No	Whether the firm deals with virtual assets

`risk_assessment`

Assess compliance risk of a planned business activity. Returns Red/Yellow/Green risk rating with regulatory basis and recommended actions.

Parameter	Required	Description
`description`	Yes	Description of the planned business activity
`license_types`	No	Relevant license types
`urgency`	No	`"immediate"`, `"planned"`, `"exploratory"`

Example Queries

Licensing & Exams

What exams do I need for an SFC Type 9 (Asset Management) license?
→ Complete exam structure, pass marks, exemption conditions, official links

Enforcement Intelligence

Search for SFC enforcement actions related to AML in 2025
→ Matching cases with companies, penalties, regulatory basis, official notices

Bilingual Regulatory Updates

SFC最新的通函和監管動態是什麼？
→ 最新通函列表，含參考編號、日期、主題、官方文件鏈接（繁體中文）

Compliance Health Check

Run a compliance check for a Type 1 + Type 9 firm with 3 ROs, 25 staff, 2B HKD AUM
→ FRR capital assessment, RO configuration review, regulatory focus areas

Risk Assessment

We want to launch a tokenized fund product for retail investors in Hong Kong
→ Red/Yellow/Green rating, regulatory basis, recommended actions, timeline

Fee & Market Intelligence

What are the current RO retainer fees and shell company prices?
→ Structured fee benchmarks from vigo_fee_benchmarks with latest market data

Knowledge Base

VIGO's intelligence is powered by a structured, continuously updated knowledge base with 6,381 verified knowledge chunks covering 26 years of SFC regulatory history:

Data Sources

Official Sources (6 endpoints + HKMA)

SFC Circulars, Enforcement News, Consultation Papers
VATP/Virtual Asset regulatory updates
Press Releases and policy announcements
HKMA Joint Circulars (auto-filtered for SFC-relevant content)

Foundational Documents (35 + 5 Thematic Reports)

12 Codes + 16 Guidelines + 3 Laws (SFO, SFF, AMLO) + 2 Handbooks + 2 HKEX Listing Rules
5 SFC Thematic Inspection Reports (Cybersecurity, Sponsor Business, Prime Services, Securities Margin Financing, Alternative Liquidity Pools)

Industry Intelligence (17 sources)

International Law Firms (6): Charltons, Deacons, KWM, Sidley Austin, Linklaters, Clifford Chance
Local Law Firms (3): ONC Lawyers, Stevenson Wong, Paradox Management
Big 4 (4): Deloitte HK, PwC HK, EY HK, KPMG HK
Compliance Consultants (2): CompliancePlus, Waystone
Compliance Tech (2): Heinbro, BBCIncorp

v7.0 Structured Data (76 records)

Table	Records	Content
`vigo_enforcement`	28	Structured enforcement records (entity, violations, penalties, bans)
`vigo_regulations`	21	Structured regulation documents (categories, effective dates, requirements)
`vigo_fee_benchmarks`	25	Fee benchmarks (RO retainers, SFC fees, application costs)
`vigo_license_market`	2	License market pricing (shell prices, transaction data)

Coverage

All SFC license types (Type 1–13) and VATP licensing
AML/CFT guidelines and enforcement case history
Exam requirements, CPD/CPT rules, fit-and-proper criteria
FRR capital requirements and operational compliance
HKEX Main Board and GEM Listing Rules
Cross-border: Stock Connect, MRF Fund Mutual Recognition, WMC

Quality Assurance

Metric	Target	Actual	Status
Duplication rate	≤ 2%	1.0%	✅ World-Class
GOLD verification rate	≥ 60%	64.8% (4,155 records)	✅ World-Class
Freshness score	≥ 0.95	0.987	✅ World-Class
Authority score	≥ 80	85.6	✅ World-Class
Recall@5	≥ 70%	80%	✅ World-Class
MRR	≥ 0.700	0.800	✅ World-Class

Verification Grading

🥇 GOLD (authority ≥ 90): 4,155 records (65%) — SFC official, HKMA, HKEX
🥈 SILVER (authority ≥ 65): 2,226 records (35%) — Law firms, Big 4, consultants
🥉 BRONZE (authority < 65): 0 records

Quality Framework

Three-layer deduplication: L1 ref_id exact match → L2 SHA-256 content hash → L3 semantic similarity > 0.92
Six-point content validation on every chunk before upload
Five-tier authority scoring: Primary legislation (100) → Senior speeches/Big 4 (80-90) → Specialist firms (68-75) → Brokers/media (50-55) → Social/AI (5-25)
Bilingual: every entry exists in English and Traditional Chinese

v7.0 Intelligent Engine

Six-Layer Retrieval Pipeline

Query → [Layer 1] Query Router (9 route types)
      → [Layer 2] Hybrid Retrieval (Dense cosine@0.25 top20 + BM25 sparse top15)
      → [Layer 3] RRF Fusion (K=60, structured results get 1.5× boost)
      → [Layer 4] Score Fusion (rerank×0.50 + verification×0.20 + freshness + authority)
      → [Layer 5] Diversity Filter (min 3 sources, max 2 per source, cross-contamination penalty)
      → [Layer 6] Dynamic TopK (6-8 results based on query complexity)
      → Answer with citations

Dual-Model Routing

Model	Use Case	Trigger
GPT-4o-mini	Fast lookups, simple facts	capital_requirement / fee_benchmark / enforcement_lookup / license_market
DeepSeek Chat	Deep analysis, regulatory interpretation	comparison / how_to / general / latest_update

Built-in fallback: if GPT-4o-mini fails → auto-switch to DeepSeek.

9 Query Route Types

Each route type has optimised search weights (freshness, authority) and strategy (structured_lookup / semantic / multi_query / hybrid):

capital_requirement · license_market · enforcement_lookup · fee_benchmark · latest_update · comparison · how_to · general · unknown

Six-Layer Anti-Hallucination

LICENSE_TYPE_MAP hardcoded — all SFC exam subjects verified against HKSI website 2026
System Prompt strict instructions — never supplement specific numbers from training data
Reranking filter — demote non-matching license type documents
Verification grade weighting — GOLD > SILVER > BRONZE
Cross-contamination penalty — -0.05 for mismatched license documents
Diversity filter — force minimum 3 different sources

Iceberg Strategy (Response Philosophy)

Layer	Description	Role
Step 1: Direct Answer	Clear numbers, legal provisions, processes	Compliance Officer
Step 2: Market Calibration	Reference latest market data and fee benchmarks	Analyst
Step 3: Strategic Extension	"From an Optimization perspective, also consider..."	Architect

Autonomous Operations

v7.0 achieves fully autonomous operations with zero manual intervention:

pg_cron Scheduled Tasks (4)

Task	Schedule	Function
Daily freshness update	`0 3 * * *`	Recalculate freshness_score
Weekly duplicate detection	`0 4 * * 0`	Flag is_duplicate
Monthly statistics	`0 5 1 * *`	Update vigo_stats
Quarterly cleanup	`0 6 1 1,4,7,10 *`	Clean expired memory

GitHub Actions Three-Tier Scheduling

Workflow	Schedule	Tasks	Duration
`vigo-daily.yml`	Sun-Thu 23:00 UTC	Mode 1 daily sync + Mode 14a conflict detection	~16 min
`vigo-weekly.yml`	Sun 00:00 UTC	Mode 13e data quality + Mode 14e full inspection	~45 min
`vigo-monthly.yml`	15th 00:00 UTC	Mode 6+9+13e+12e+11a comprehensive maintenance	~60 min

Monthly GitHub Actions usage: ~350 minutes (well within free tier of 2,000 minutes).

Collection Pipeline

auto_collect_upload.py v7.0.3 (6,292 lines) supports 14+ modes:

Mode	Function	Frequency
Mode 1	SFC latest updates (6 official endpoints + HKMA)	Daily (auto)
Mode 2	Historical deep scan (1m/3m/6m/1y)	Quarterly
Mode 3	Local PDF import	On-demand
Mode 4	Practical experience import (16 templates)	Ongoing
Mode 5	Foundational documents import + health check	Monthly
Mode 6	Industry intelligence scan (17 sources)	Monthly (auto)
Mode 7	Universal file importer (PDF/DOCX/XLSX/TXT/MD)	On-demand
Mode 8	Database management	Monthly
Mode 9	Knowledge base update	Monthly (auto)
Mode 11	Evaluation benchmark (50 questions)	Monthly (auto)
Mode 12	Structured data extraction → 4 tables	Monthly (auto)
Mode 13	Data quality engine — full scan + repair	Weekly (auto)
Mode 14	Self-correction engine — conflict detection + inspection	Daily/Weekly (auto)

Architecture

┌─────────────────────────────────────────────┐
│  MCP Clients                                │
│  Claude · ChatGPT · Cursor · VS Code       │
│  Claude Code · Any MCP Client               │
└──────────────────┬──────────────────────────┘
                   │ MCP Protocol (Streamable HTTP)
                   ▼
┌─────────────────────────────────────────────┐
│  VIGO MCP Server v2.1 (6 tools, 582 lines) │
│  Supabase Edge Function (Deno TypeScript)   │
└──────────────────┬──────────────────────────┘
                   │
    ┌──────────────┼──────────────┐
    ▼              ▼              ▼
 OpenAI        Supabase       DeepSeek + GPT-4o-mini
 Embeddings    PostgreSQL     Dual-Model Routing
 (1536-dim)    pgvector       (with auto-fallback)
               + BM25 FTS

┌─────────────────────────────────────────────┐
│  vigo-chat v5.2 (1,032 lines)               │
│  Query Router (9 types) → Hybrid Retrieval  │
│  → RRF Fusion → Score Fusion → Diversity    │
│  → Dual-Model → Engram Memory → Response    │
└─────────────────────────────────────────────┘

┌─────────────────────────────────────────────┐
│  vigo-ingest v6.1.2 (458 lines)             │
│  Auto-classify → Semantic chunk → Verify    │
│  → Grade (GOLD/SILVER/BRONZE) → Store       │
│  → Auto-generate quick questions             │
└─────────────────────────────────────────────┘

┌─────────────────────────────────────────────┐
│  Autonomous Operations                      │
│  pg_cron (4 tasks) + GitHub Actions (3)     │
│  auto_collect_upload.py v7.0.3 (6,292 lines)│
│  14+ modes · Fully autonomous · Zero manual │
└─────────────────────────────────────────────┘

Edge Functions

Function	Version	Lines	Purpose
`vigo-chat`	v5.2	1,032	Main API: query → embedding → hybrid retrieval → dual-model routing → answer
`vigo-mcp`	v2.1	582	MCP server: 6 tools, Streamable HTTP, authority-weighted post-processing
`vigo-ingest`	v6.1.2	458	Intelligent ingest: filter → classify → deduplicate → verify → extract
`vigo-quick-questions`	v1.0	143	Personalised follow-up question recommendations via Engram

Database

Table	Purpose
`vigo_knowledge`	6,381 knowledge chunks with embeddings (vector 1536), authority scores, verification grades
`vigo_enforcement`	28 structured enforcement records
`vigo_regulations`	21 structured regulation documents
`vigo_fee_benchmarks`	25 fee benchmark records
`vigo_license_market`	2 license market pricing records
`vigo_conversation_memory`	Engram: conversation history with semantic vectors
`vigo_user_preferences`	Engram: user language and interest preferences
`vigo_learning_progress`	Engram: topic understanding levels

Transport: Streamable HTTP (MCP standard)
Authentication: None required
Runtime: Supabase Edge Functions (Deno TypeScript)

Note: The MCP server is the open, stateless interface for any AI client. On the OrphicOne platform, VIGO also integrates Engram — a long-term memory system that stores conversation history, tracks user preferences, and adapts responses based on learning progress. Engram uses semantic retrieval (vector similarity) over past dialogues to deliver increasingly personalised compliance guidance over time.

Distribution

Channel	Status	Notes
MCP Official Registry	✅ Active	Core channel, auto-synced by downstream platforms
Smithery	✅ Published	All 6 tools recognised
Glama	✅ Listed	Connector verification passed
Anthropic Connectors	✅ Live	Highest traffic channel
PulseMCP	⏳ Auto-syncing	Pulls from Registry
`.well-known`	✅ Configured	Supports auto-discovery

Version History

Version	Date	Highlights
v7.0	2026-02-24	Sprint 1-4 (structured extraction + quality engine + self-correction + evaluation benchmarks), autonomous ops (pg_cron + GitHub Actions), dual-model routing, 6,292 lines
v6.0	2026-02-23	Six-layer intelligent retrieval, three-tier verification, hybrid search, vigo-ingest, reference engine, 4,547 lines
v5.1	2026-02-21	AI RO reasoning framework, compliance_check, risk_assessment, MCP tools 4→6
v5.0	2026-02-20	Quality assurance framework, three-layer dedup, six-point validation, 35 foundational docs
v3.2	2026-02-03	Architecture upgrade: DeepSeek/OpenAI direct connection, 50%+ latency reduction
v3.0	2026-02-03	Anti-hallucination System Prompt + reranking filter
v2.0	2026-01-31	Engram memory system full integration
v1.0	2026-01-29	Initial release: basic RAG functionality

About

OrphicOne is a Hong Kong-based regulatory intelligence platform for financial services.

VIGO is OrphicOne's AI-powered regulatory intelligence agent — the industry's first and currently only MCP server dedicated to financial regulatory intelligence in any jurisdiction.

Positioning

Among 16,000+ MCP servers globally, VIGO occupies a unique position:

Global MCP Ecosystem (16,000+ servers)
├── Developer Tools        ████████████████  thousands
├── Productivity           ██████████        hundreds
├── Data & Analytics       ████████          hundreds
├── Financial Reg Intelligence █                 VIGO (only one)
└── HK SFC Reg Intelligence    █                 VIGO (industry first)

Data Moat

26 years of SFC regulatory history (2000–2026)
6,381 verified knowledge chunks with three-tier quality grading
76 structured records across 4 specialised tables (enforcement, regulations, fees, market)
35 foundational documents + 5 thematic inspection reports
17 industry sources crawled monthly with sub-page extraction
HKMA joint circulars + HKEX listing rules cross-referenced
Three-layer deduplication + six-point content validation
v7.0 intelligent engine with dual-model routing, self-correction, and autonomous operations
World-Class benchmarks: Recall@5 80%, MRR 0.800, duplication 1.0%, GOLD rate 64.8%
Knowledge that took years of domain expertise to curate — not easily replicated

Philosophy

VIGO is built on the belief that compliance is not a cost — it is a competitive advantage. Great compliance doesn't slow business down; it provides the foundation for sustainable growth, client trust, and market credibility.

Compliance is the floor (The Floor), ensuring safety. Business is the ceiling (The Ceiling), achieving breakthroughs. Grounded in compliance, fluent in capital. Compliance as shield, business as spear.

Roadmap

Phase	Focus	Status
Phase 1	SFC compliance — all license types, enforcement, VATP, v7 engine, 35 foundational docs, 5 thematic reports, 17 industry sources, QA framework, autonomous ops, dual-model routing, structured data extraction	✅ Live (v7.0)
Phase 2	Full HK regulatory coverage (HKMA, IA, MPFA)	Planned (2026)
Phase 3	Cross-border Asia-Pacific (Singapore MAS, Dubai VARA)	Future (2027)
Phase 4	Global digital asset regulatory intelligence	Vision (2028+)

Privacy

VIGO is a read-only regulatory intelligence service. We do not collect personal information, store conversation data, or require authentication. All query tools are marked readOnlyHint: true. See our Privacy Policy.

VIGO provides regulatory information query services only and does not constitute legal or financial advice. Users should treat VIGO's answers as reference and consult professional compliance advisors or lawyers when necessary.

Support

License

MIT

Name		Name	Last commit message	Last commit date
Latest commit History 39 Commits
.github/workflows		.github/workflows
.mcp		.mcp
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
auto_collect_upload.py		auto_collect_upload.py
eval_questions.json		eval_questions.json
server.json		server.json

License

OrphicOne-Platform/vigo-mcp

Folders and files

Latest commit

History

Repository files navigation

VIGO — The First MCP Server for Financial Regulatory Intelligence

What is VIGO?

V.I.G.O. — The Four Dimensions

Why VIGO instead of asking Claude/ChatGPT directly?

Quick Start

Claude (Web, Desktop, Mobile)

Cursor

VS Code

Claude Code

ChatGPT Desktop

Tools

query_regulation

search_enforcement

get_license_guide

latest_updates

compliance_check

risk_assessment

Example Queries

Knowledge Base

Data Sources

v7.0 Structured Data (76 records)

Coverage

Quality Assurance

v7.0 Intelligent Engine

Six-Layer Retrieval Pipeline

Dual-Model Routing

9 Query Route Types

Six-Layer Anti-Hallucination

Iceberg Strategy (Response Philosophy)

Autonomous Operations

pg_cron Scheduled Tasks (4)

GitHub Actions Three-Tier Scheduling

Collection Pipeline

Architecture

Edge Functions

Database

Distribution

Version History

About

Positioning

Data Moat

Philosophy

Roadmap

Privacy

Support

License

About

Topics

Resources

License

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Stars

Watchers

Forks

Releases

Packages 0

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Contributors

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Languages

`query_regulation`

`search_enforcement`

`get_license_guide`

`latest_updates`

`compliance_check`

`risk_assessment`

Packages