Institutional-grade quantitative risk management, real-time market data, and deterministic financial math—all inside your Claude chat interface.
A direct bridge between LLM reasoning and professional quant systems.
Direct integration with PostgreSQL, MySQL, and Snowflake. No file uploads needed—just live data.
Real-time volatility, closing prices, and T-Bill rates via yfinance. Grounded in today's reality.
Calibrated logistic regression models for predicting default probability with rigorous math.
In-chat simulations using Matplotlib. Visualize 1,000+ paths directly in your conversation.
Local NLP models analyzing market news for quantitative bullish/bearish signals.
One-click export of RAG-colored Excel risk registers and KRI dashboards.
Proof-of-work: Kupiec POF tests to validate your Risk Models against the Basel Traffic Light system.
Institutional privacy by design. Monte Carlo models and SQL queries execute 100% locally.
18 institutional tools for full-spectrum risk oversight.
Background intelligence that runs on every response.
Adds a 📊 AEGIS RISK SNAPSHOT (5x5 Matrix) to every risk-related response.
ALWAYS-ONScan-on-upload detection for liability, indemnification, and force majeure clauses.
AUTOMATICFlags GDPR, PSD2, DORA, Basel, NIS2, and EMIR exposure automatically.
COMPLIANCEInstantly translates technical quant findings for executive and board-level understanding.
REPORTINGFollow these simple steps to empower your Claude instance with institutional risk intelligence.
Open your claude_desktop_config.json and add the Aegis MCP server configuration.
"vkkm-aegis": {
"command": "npx",
"args": ["-y", "vkkm-aegis"]
}
Restart Claude and run your first command, for example /vkkm:stress-test, to
initialize the local Python backend.
Use the local environment variables to securely store your SQL connection strings for seamless integration.