# Incident to Claim Timeline AI Agent Connect

> Incident to Claim Timeline MCP organizes fragmented insurance data into a single, chronological record. Your AI client uses this to merge incident events, witness statements, and policy milestones into a factual sequence. It helps you verify reporting compliance and track the time elapsed since an incident occurred.

## Overview
- **Category:** productivity
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_2Jx6ihn98xkUk9Lf9bICcAqcS6Mbi25uuOVI1DYW/ai-agent-connect
- **Tags:** claims, timeline, insurance, compliance, chronology

## Description

Managing insurance claims often means digging through a disorganized pile of dates, notices, and statements. This MCP fixes that by reconstructing a complete, ordered history from your raw data. You can feed your agent various data points, and it will build a single timeline that shows exactly how an incident progressed through the policy lifecycle. 

Instead of manually checking if a notice was sent on time, your AI client can run compliance checks against policy milestones. You can also isolate specific parts of the history, like just the witness statements or just the policy notices, to get a clearer view of specific phases. It turns a collection of disconnected timestamps into a logical narrative that makes sense for claims adjusting and auditing.

## Tools

### summarize_claim_status
This tool provides a high-level narrative of the time elapsed between the initial incident and the current status.

### filter_timeline_by_type
Use this to extract a specific subset of the timeline, such as only notices or only policy milestones.

### get_chronological_timeline
This tool reconstructs a complete, ordered history using all the incident-related data points you provide.

### validate_reporting_compliance
This tool checks if a claim was reported within the specific timeframes required by policy milestones.

## Prompt Examples

**Prompt:** 
```
Create a timeline from these events: Incident on 2023-01-01 (Burst Pipe), Policy Effective on 2022-12-01, and Notice sent on 2023-01-05.
```

**Response:** 
```
1. 2022-12-01: Policy Effective (Policy)
2. 2023-01-01: Burst Pipe (Incident)
3. 2023-01-05: Notice sent (Notice)
```

**Prompt:** 
```
Was the claim reported within 3 days of the incident? Incident: 2023-05-10, Notice: 2023-05-12.
```

**Response:** 
```
The claim is Compliant. The notice was reported 2 days after the incident.
```

**Prompt:** 
```
Summarize the status for a timeline where the incident was 2023-06-01 and today is 2023-06-10.
```

**Response:** 
```
Total days since incident: 9. The incident occurred 9 days ago.
```

## Capabilities

### Timeline Reconstruction
Your agent builds a full, ordered history from scattered incident data.

### Compliance Checking
The AI verifies if reporting happened within required policy windows.

### Data Filtering
Your client isolates specific categories like notices or milestones from the full timeline.

### Status Summarization
The agent generates a narrative of the time passed since the incident occurred.

## Use Cases

### Reporting Compliance Audits
Check if a claimant reported an incident within the mandatory window defined in their policy.

### Claim History Reconstruction
Turn a list of messy, unorganized incident notes into a clean, ordered timeline.

### Timeline Categorization
Isolate only the policy milestones or only the witness statements from a long claim history.

### Aging Analysis
Get a quick summary of how many days have passed since an incident occurred to track claim aging.

## Benefits

- Converts disconnected timestamps into a single chronological sequence.
- Automates the verification of reporting windows against policy rules.
- Reduces manual sorting by filtering timelines by specific event types.
- Provides instant narrative summaries of time elapsed since an incident.

## How It Works

Get your insurance data organized in minutes by connecting this MCP to your preferred AI client.

1. Connect the MCP to your AI client via Vinkius.
2. Provide your incident data, witness statements, or policy milestones to your agent.
3. Ask your agent to build a timeline or check for compliance.
4. Review the structured, chronological output or narrative summary.

## Frequently Asked Questions

**What can this MCP do with my insurance data?**
It sequences incident events, witness statements, and policy milestones into a single, ordered timeline. It can also check for reporting compliance and summarize the time elapsed since an incident.

**Which AI clients can I use with this MCP?**
You can use this MCP with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

**How does it check for compliance?**
The tool compares the date an incident was reported against the required timeframes defined in your policy milestones.

**Can I filter the timeline for specific events?**
Yes, you can use the filter tool to isolate specific categories like notices or policy milestones from the full history.

**Do I need to host this myself?**
No, Vinkius hosts and manages the MCP for you. You just connect your client and start using the tools.

**How do I create a chronological sequence of events?**
Use the `get_chronological_timeline` tool by providing the incident events, witness statements, notices, and policy milestones as JSON strings.

**Can I check if a claim was reported on time?**
Yes, use the `validate_reporting_compliance` tool to compare the earliest incident event against the earliest notice based on your specified deadline.

**How can I get a summary of the time elapsed since the incident?**
You can use `summarize_claim_status` with the generated timeline and a target date to receive a narrative summary and total days elapsed.