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🤖🕰️ An MCP server that gives language models temporal awareness and time calculation abilities. Teaching AI the significance of the passage of time through collaborative tool development.
| Date | Stars |
|---|---|
| 2026-07-31 | 715 |
| 2026-08-01 | 715 |
| 2026-08-06 | 715 |
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# "Passage of Time" Model Context Protocol (MCP) Server 🕐
An MCP server that gives language models temporal awareness and time calculation abilities. Teaching LLMs the significance of the passage of time through collaborative tool development.
## 📖 The Story
This project emerged from a philosophical question: "Can AI perceive the passage of time?" What started as an exploration of machine consciousness became a practical solution to a real problem - LLMs can't reliably calculate time differences.
Instead of publishing a paper about how "silly" these models are at mental math, we decided to do what we've done for ourselves: **equip them with a calculator for time**.
Through human-LLM collaboration, we discovered that with proper temporal tools, models can uncover surprising insights about conversation patterns, work rhythms, and the human experience of time.
[Read the full story on Medium →](https://medium.com/@jeremie.lumbroso/teaching-ai-the-significance-of-the-passage-of-time-yes-that-one-106ad7d20957)
## 🚀 Quick Start
### Prerequisites
- Python 3.12+
- pipenv (or pip)
- An MCP-compatible client (Claude.ai, Continue.dev, etc.)
### Installation
1. Clone the repository:
```bash
git clone https://github.com/jlumbroso/passage-of-time-mcp.git
cd passage-of-time-mcp
```
2. Install dependencies:
```bash
pipenv install
# or with pip:
pip install fastmcp pytz
```
3. Run the server:
```bash
pipenv run server
# or directly:
pipenv run python passage_of_time_mcp.py
```
The server will start on `http://0.0.0.0:8000/sse`.
### Connecting to Claude.ai
1. In Claude.ai, go to Settings → Integrations
2. Click "Add integration" and select "Custom"
3. Enter the server URL (e.g., `https://your-server.ngrok-free.app/sse` if using ngrok, make sure to add `/sse` at the end)
4. Save and enable all the time-related tools
> **Note**: For local development, you'll need to expose your server using ngrok or deploy it to a public URL.
## 🛠️ Available Tools
### Core Functions
#### `current_datetime(timezone="America/New_York")`
Returns the current date and time. The foundation of temporal awareness.
```
Returns: "2024-01-15 14:30:45 EST"
```
#### `time_difference(timestamp1, timestamp2, unit="auto")`
Calculates the duration between two timestamps with human-readable output.
```python
# Example response:
{
"seconds": 11401,
"formatted": "3 hours, 10 minutes, 1 second",
"requested_unit": 3.17, # if unit="hours"
"is_negative": false
}
```
#### `timestamp_context(timestamp)`
Provides human context about a timestamp - is it weekend? Business hours? Dinner time?
```python
# Example response:
{
"time_of_day": "evening",
"day_of_week": "Saturday",
"is_weekend": true,
"is_business_hours": false,
"typical_activity": "leisure_time",
"relative_day": "today"
}
```
#### `time_since(timestamp)`
Calculates how long ago something happened with contextual descriptions.
```python
# Example response:
{
"seconds": 7200,
"formatted": "2 hours ago",
"context": "earlier today"
}
```
#### `parse_timestamp(timestamp)`
Converts timestamps between different formats for maximum compatibility.
```python
# Example response:
{
"iso": "2024-01-15T14:30:45-05:00",
"unix": "1705343445",
"human": "January 15, 2024 at 2:30 PM EST",
"day_of_week": "Monday"
}
```
#### `add_time(timestamp, duration, unit)`
Adds or subtracts time with natural language descriptions.
```python
# Example response:
{
"result": "2024-01-16 14:30:45",
"iso": "2024-01-16T14:30:45-05:00",
"description": "tomorrow at 2:30 PM"
}
```
#### `format_duration(seconds, style="full")`
Formats durations in various styles for different contexts.
```python
# style="full": "2 hours, 30 minutes, 15 seconds"
# style="compact": "2h 30m 15s"
# style="minimal": "2:30:15"
```
## 💡 Example Conversations
### Basic Time Awareness
```
Human: What time is it?
Claude: [Excerpt of 12,203 characters
Read on GitHub
4
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