# Task Delay Days MCP for scheduling. AI Agent Connect

> Task Delay Days MCP gives your AI client the ability to measure the gap between planned and actual task completion. It calculates specific day variances, checks if delays stay within your set tolerance levels, and tracks how schedule slips accumulate over months. You can use it to get high-level project health summaries or drill down into individual task performance.

## Overview
- **Category:** productivity
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_8uquYOmd7IlWn4Dzio1RJUdlKI55LrKVsUDO4eVp/ai-agent-connect
- **Tags:** scheduling, delay-calculation, project-health, variance-analysis, timeline

## Description

You can stop guessing why your project timelines are slipping. This MCP gives your AI client the math it needs to pinpoint exactly where your schedule is breaking down. Instead of manually comparing dates, you can ask your agent to calculate the specific number of days a task is late or early. If you need to see if a delay actually matters, the MCP checks it against your predefined tolerance thresholds to see if it's a minor hiccup or a compliance issue. For a broader view, you can pull a summary of delays across multiple tasks to gauge overall project health or look at monthly trends to see if your delays are getting worse over time. It turns raw date data into actionable schedule intelligence.

## Tools

### check_schedule_compliance
This tool checks if a task or group of tasks stays within your allowed delay limits. It compares actual delays against your specific tolerance thresholds.

### get_batch_delay_summary
This tool aggregates delay data from several tasks at once. It provides a high-level look at the overall health of your project schedule.

### get_project_delay_trend
This tool tracks how delays accumulate over time. It groups task delays by their planned completion months to show you monthly trends.

### get_task_delay
This tool calculates the exact number of days a single task is either late or ahead of schedule.

## Prompt Examples

**Prompt:** 
```
How many days was the task delayed if it was planned for 2024-05-01 and finished on 2024-05-05?
```

**Response:** 
```
The task was delayed by 4 days.
```

**Prompt:** 
```
Is a task compliant if it was planned for 2024-06-10, finished on 2024-06-12, and my tolerance is 3 days?
```

**Response:** 
```
Yes, the task is compliant as the 2-day delay is within the 3-day tolerance.
```

**Prompt:** 
```
What is the total delay for these tasks: [{ 'plannedDate': '2024-01-01', 'actualDate': '2024-01-05' }, { 'plannedDate': '2024-01-10', 'actualDate': '2024-01-08' }]?
```

**Response:** 
```
The total delay is 2 days.
```

## Capabilities

### Individual Variance Calculation
Your agent uses this to find the exact day count for a single task's delay.

### Threshold Validation
The AI checks if specific delays violate your project's set tolerance levels.

### Project Health Aggregation
Your agent pulls a summary of delays across many tasks to assess the whole project.

### Monthly Trend Analysis
The AI identifies if delays are increasing or decreasing by grouping them by month.

## Use Cases

### Identifying Bottlenecks
Use the tool to find which specific tasks are consistently exceeding their planned dates.

### Monthly Performance Reviews
Generate a report on how delays have accumulated month over month to spot growing issues.

### Compliance Auditing
Check a batch of completed tasks to see if they all stayed within the allowed delay window.

### Project Health Reporting
Get a quick summary of total delays to present a status update to stakeholders.

## Benefits

- Replaces manual date subtraction with direct tool calls.
- Identifies cumulative monthly delays through automated grouping.
- Automates compliance checks against custom tolerance thresholds.
- Provides high-level project health summaries from raw task data.

## How It Works

Connect the MCP to your client and start asking questions about your task data.

1. Connect your MCP-compatible client to Vinkius.
2. Provide your task data or schedule details to your AI agent.
3. Ask the agent to calculate delays or check compliance.
4. The agent calls the specific tool to process the dates.
5. Receive a direct answer about task variances or project trends.

## Frequently Asked Questions

**How does this MCP calculate task delays?**
It calculates the difference in days between the planned completion date and the actual completion date.

**Can I check if a delay is acceptable?**
Yes, you can use the compliance tool to see if a delay falls within your specific tolerance threshold.

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

**Can it show me trends over time?**
Yes, the tool can group delays by their planned completion months to show how they accumulate.

**Do I need to host this myself?**
No, Vinkius hosts and manages the MCP for you, so it is ready to use immediately after connection.

**How do I calculate the delay for a single task?**
You can use the `get_task_delay` tool by providing the planned completion date and the actual completion date in ISO 8601 format.

**Can I check if my project is within its allowed delay threshold?**
Yes, the `check_schedule_compliance` tool allows you to define a tolerance in days to see if a task is compliant or exceeds the limit.

**How can I see the trend of delays over several months?**
The `get_project_delay_trend` tool aggregates task delays and groups them by the month of their planned completion date.