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Agent-Optimized Interface

This page is designed for parallel human-agent interaction

FinX AMP Products

Agentic Quant Analytics for Capital Markets

FinX AMP Platform

The Agent Modeling Platform - cloud-native quantitative analytics specifically designed for AI agents and their human operators. Parallel interfaces enable agents to access structured data while humans utilize intuitive dashboards.

Built around the FinX Library with agent-first architecture, AMP creates ultra-fast workflows for complex financial instruments with both programmatic agent access and human-readable interfaces.

RMBS Portfolio Analytics
// Processing 5,000 mortgage-backed securities // Running advanced prepayment models and stress tests // Grid computing resources: 128 cores allocated
Prepayment Speeds (CPR)

8.7% (Current) | 12.3% (Forecast)

Yield Analysis

4.32% (Option-Adjusted Spread)

Duration Risk

2.7 yrs (Base) | 3.4 yrs (Stressed)

Credit Performance

0.8% (Default Rate) | 65% (Recovery)

Calculation complete: 5,000 securities processed in 47 seconds Stress test scenarios: 20/20 passed | Report generation: COMPLETED

Need help choosing the right product?

Our team is ready to help you find the perfect solution for your agent-human workflows.

Agent Interface
Structured data access for AI agents

Context: FinX AMP platform

REST API Endpoints

POST /api/amp/portfolio/analyze

Portfolio analytics

GET /api/amp/instruments/{security_id}

Instrument data

POST /api/amp/risk/calculate

Risk calculations
Headers: Authorization: Bearer FINX_API_KEY
MCP Server Connection

finx-mcp://api.finx.io/mcp

Protocol: Model Context Protocol v1.0
Available Resources:portfolio/holdingsrisk/scenariosanalytics/results
Agent Connection Status

Ready for Agent Connection

Both REST and MCP interfaces available
// Sample Agent Integration
// REST API
const response = await fetch(
  '/api/analytics/FinX-AMP platform',
  { headers: { 'Authorization': 'Bearer FINX_API_KEY' } }
);

// MCP Connection  
const mcp = new MCPClient('finx-mcp://api.finx.io/mcp');
await mcp.connect();
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