# Time MCP Server (`agentify/time-mcp-server`) Actor

An MCP server implementing the Model Context Protocol (MCP) for time-related operations.

- **URL**: https://apify.com/agentify/time-mcp-server.md
- **Developed by:** [agentify](https://apify.com/agentify) (community)
- **Categories:** MCP servers, AI, Open source
- **Features:** Full permissions, Single-tenant, Server interface
- **Stats:** 9 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 get current times

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## ⏰ Time MCP Server (Apify Actor)

This Actor provides a Model Context Protocol (MCP) server for time and timezone conversion, running on the Apify platform. It enables LLMs and other clients to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.

***

### 🚩 Claim this MCP server

All credits to the original authors of <https://github.com/modelcontextprotocol/servers/tree/main/src/time>
To claim this server, please write to <ai@apify.com>.

***

### Features

- **Current time lookup** in any IANA timezone
- **Timezone conversion** between arbitrary IANA timezones
- **Automatic system timezone detection** (can be overridden)
- **Stdio MCP server** integration (runs `mcp-server-time` via `uvx`)
- **Pay Per Event (PPE) billing** for each tool call
- **Ready for Claude, Zed, VS Code, and other MCP clients**

***

### Available Tools

- `get_current_time` – Get current time in a specific timezone or system timezone
  \- Arguments: `timezone` (string, IANA name, e.g. 'Europe/London')
- `convert_time` – Convert time between timezones
  \- Arguments: `source_timezone` (string), `time` (string, HH:MM), `target_timezone` (string)

***

### Usage

#### Local run

```sh
apify run -p
```

#### Example Interactions

**Get current time:**

```json
{
    "name": "get_current_time",
    "arguments": { "timezone": "Europe/Warsaw" }
}
```

**Convert time:**

```json
{
    "name": "convert_time",
    "arguments": {
        "source_timezone": "America/New_York",
        "time": "16:30",
        "target_timezone": "Asia/Tokyo"
    }
}
```

***

### Configuration

By default, the Actor launches `mcp-server-time` via `uvx` (recommended). To override the system timezone, set the `--local-timezone` argument in the command.

For pip installs, adjust the command to `python` and args to `['-m', 'mcp_server_time']` in both `src/main.py` and your client config.

***

### Billing (Pay Per Event)

Each tool call is billed per event. See `.actor/pay_per_event.json` and `src/const.py`:

```json
{
    "get_current_time": { "price": 0.0005 },
    "convert_time": { "price": 0.0005 }
}
```

***

### Links & Resources

- [MCP servers repo](https://github.com/apify/mcp-servers)
- [MCP docs](https://mcp.apify.com)
- [Model Context Protocol](https://modelcontextprotocol.io)
- [Apify SDK for Python](https://docs.apify.com/sdk/python)

***

### Claim this server

To claim ownership or manage this MCP server, visit the [Model Context Protocol claim page](https://github.com/modelcontextprotocol/servers/tree/main/src/time).

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("agentify/time-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("agentify/time-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call agentify/time-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentify/time-mcp-server"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/EMrDENM3zwjUDtpqS/builds/r7oHJrgo54Y72r5VN/openapi.json