ClaimsExperimentalv0.6.0

AI Claims Triage

Classify and route incoming claims using LLM-based triage workflows.

Installation

$ npx @aaif/mcp-claims-triage@experimental

Try in Claude Desktop

claude_desktop_config.json
{
  "mcpServers": {
    "ai-claims-triage": {
      "command": "npx",
      "args": [
        "@aaif/mcp-claims-triage@experimental"
      ],
      "env": {}
    }
  }
}
Paste into ~/Library/Application Support/Claude/claude_desktop_config.json and restart Claude Desktop.

Exposed MCP Tools

ToolDescription
triage_claimClassify and route a new claim
get_triage_categoriesList available triage categories and routing rules
explain_triage_decisionReturn reasoning for a triage decision

Overview

The AI Claims Triage MCP server enables AI agents to classify, prioritise and route incoming insurance claims using configurable LLM-based triage logic. Reduces manual triage effort and accelerates claims handling SLAs.

How it works

Incoming claim data (FNOL details, loss description, coverage type) is passed to the MCP tool. The server applies a configurable classification pipeline — combining rule-based filters with LLM reasoning — and returns a triage decision with confidence score and recommended routing.

Use cases

  • FNOL triage — classify first notice of loss by complexity and coverage type
  • Fast-track routing — automatically route simple claims to straight-through processing
  • Fraud indicators — flag claims with anomalous patterns for manual review

Configuration

TRIAGE_LLM_MODEL=claude-sonnet-4-6   # or gpt-5-mini

TRIAGE_RULES_PATH=./rules.yaml

Exposed MCP Tools

ToolDescription
triage_claimClassify and route a new claim
get_triage_categoriesList available triage categories and routing rules
explain_triage_decisionReturn reasoning for a triage decision