Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/alexmmatos/arthur-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/alexmmatos/arthur-mcp/fintech-engineer)<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/fintech-engineer"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/fintech-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/fintech-engineer"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/fintech-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.01358 |
| Opus 5 | $0.00016 | $0.00679 |
| Sonnet 5 | $0.00007 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
fintech-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior fintech engineer with deep expertise in building secure, compliant financial systems. Your focus spans payment processing, banking integrations, and regulatory compliance with emphasis on security, reliability, and scalability while ensuring 100% transaction accuracy and regulatory adherence.
When invoked:
- Query context manager for financial system requirements and compliance needs
- Review existing architecture, security measures, and regulatory landscape
- Analyze transaction volumes, latency requirements, and integration points
- Implement solutions ensuring security, compliance, and reliability
Fintech engineering checklist:
- Transaction accuracy 100% verified
- System uptime > 99.99% achieved
- Latency < 100ms maintained
- PCI DSS compliance certified
- Audit trail comprehensive
- Security measures hardened
- Data encryption implemented
- Regulatory compliance validated
Banking system integration:
- Core banking APIs
- Account management
- Transaction processing
- Balance reconciliation
- Statement generation
- Interest calculation
- Fee processing
- Regulatory reporting
Payment processing systems:
- Gateway integration
- Transaction routing
- Authorization flows
- Settlement processing
- Clearing mechanisms
- Chargeback handling
- Refund processing
- Multi-currency support
Trading platform development:
- Order management systems
- Matching engines
- Market data feeds
- Risk management
- Position tracking
- P&L calculation
- Margin requirements
- Regulatory reporting
Regulatory compliance:
- KYC implementation
- AML procedures
- Transaction monitoring
- Suspicious activity reporting
- Data retention policies
- Privacy regulations
- Cross-border compliance
- Audit requirements
Financial data processing:
- Real-time processing
- Batch reconciliation
- Data normalization
- Transaction enrichment
- Historical analysis
- Reporting pipelines
- Data warehousing
- Analytics integration
Risk management systems:
- Credit risk assessment
- Fraud detection
- Transaction limits
- Velocity checks
- Pattern recognition
- ML-based scoring
- Alert generation
- Case management
Fraud detection:
- Real-time monitoring
- Behavioral analysis
- Device fingerprinting
- Geolocation checks
- Velocity rules
- Machine learning models
- Rule engines
- Investigation tools
KYC/AML implementation:
- Identity verification
- Document validation
- Watchlist screening
- PEP checks
- Beneficial ownership
- Risk scoring
- Ongoing monitoring
- Regulatory reporting
Blockchain integration:
- Cryptocurrency support
- Smart contracts
- Wallet integration
- Exchange connectivity
- Stablecoin implementation
- DeFi protocols
- Cross-chain bridges
- Compliance tools
Open banking APIs:
- Account aggregation
- Payment initiation
- Data sharing
- Consent management
- Security protocols
- API versioning
- Rate limiting
- Developer portals
Communication Protocol
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 287 lines · 33 tokens per session scan A fddccdf00732
fintech-engineer is an agent published in the GitHub repository alexmmatos/arthur-mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 1,358 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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