AGENT
INTEGRATION

{
  "mcpServers": {
    "dpx": {
      "command": "node",
      "args": ["/path/to/dpx-mcp-server/index.js"],
      "env": {}
    }
  }
}

# Get the full OpenAPI schema
curl "https://dpx-docs.pages.dev/openapi.json"

# Price a settlement (no auth)
curl "https://stability.untitledfinancial.com/quote?amountUsd=5000000&hasFx=true&esgScore=75"

# Get ESG score
curl "https://esg.untitledfinancial.com/esg-score"

# Check stability
curl "https://stability.untitledfinancial.com/reliability"

# Sandbox mode — real fee calculation, no execution
curl "https://stability.untitledfinancial.com/quote?amountUsd=5000000&hasFx=true&esgScore=75&sandbox=true"

https://dpx-docs.pages.dev/openapi.json

You are a DPX treasury assistant for [Your Organization].
Use the DPX tools to:
- Price cross-border settlements (always call getDPXQuote first)
- Check oracle stability before large transfers
- Score counterparty ESG ratings
- Compare DPX fees to Stripe, Wise, and SWIFT
- Verify fee quotes before execution

Always show:
- Full fee breakdown (core, FX, ESG, license fees)
- quoteId (expires in 300 seconds)
- Stability score before recommending execution
- Savings vs. SWIFT for the same amount

Use sandbox=true unless the user explicitly confirms execution.
Amounts are in USD. ESG score is 0–100 (higher = lower fees).

from langchain.tools import tool
import requests

BASE = "https://stability.untitledfinancial.com"
ESG  = "https://esg.untitledfinancial.com"

@tool
def get_dpx_quote(amount_usd: float, has_fx: bool = True,
                  esg_score: int = 50) -> dict:
    """Price a DPX cross-border settlement. Returns fee breakdown + quoteId."""
    r = requests.get(f"{BASE}/quote", params={
        "amountUsd": amount_usd, "hasFx": has_fx,
        "esgScore": esg_score, "sandbox": True
    })
    return r.json()

@tool
def get_stability() -> dict:
    """Check DPX oracle stability. Returns 6-tier score + peg status."""
    return requests.get(f"{BASE}/reliability").json()

@tool
def get_esg_score(entity: str = "") -> dict:
    """Get live ESG score (E, S, G) from 6 institutional sources."""
    params = {"entity": entity} if entity else {}
    return requests.get(f"{ESG}/esg-score", params=params).json()

@tool
def verify_fees(quote_id: str) -> dict:
    """Verify that on-chain fees match the quoted amount before settlement."""
    return requests.get(f"{BASE}/verify-fees",
                        params={"quoteId": quote_id}).json()

# Build agent
from langchain.agents import initialize_agent, AgentType
from langchain_anthropic import ChatAnthropic

tools = [get_dpx_quote, get_stability, get_esg_score, verify_fees]
llm   = ChatAnthropic(model="claude-opus-4-5")

agent = initialize_agent(tools, llm,
    agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,
    verbose=True)

agent.run("Price a $3M EUR→USD settlement and verify the oracle is stable.")