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Schedule Task
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4 months ago
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2 months ago
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Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"liao1fan-schedule-task-mcp": {
"command": "npx",
"args": [
"-y",
"schedule-task-mcp"
],
"env": {
"SCHEDULE_TASK_DB_PATH": "YOUR_VALUE",
"SCHEDULE_TASK_TIMEZONE": "YOUR_VALUE",
"SCHEDULE_TASK_SAMPLING_TIMEOUT": "YOUR_VALUE"
}
}
}
}Schedule Task MCP is a scheduled-task management server that speaks the Model Context Protocol (MCP). It lets you create, inspect, and run jobs that trigger on intervals, cron expressions, or specific dates, while persisting state in SQLite and returning human-friendly task summaries for easy monitoring.
How to use
You interact with Schedule Task MCP through an MCP client. Start by registering the server with your client, then create and manage tasks using natural-language prompts or precise trigger configurations. Each task can run on an interval, on a cron schedule, or as a one-time date, and you can trigger runs immediately or inspect upcoming executions and history.
How to install
Prerequisites: ensure you have Node.js and npm installed on your system.
# Install the MCP server globally
npm install -g schedule-task-mcp
# Or install from source
git clone https://github.com/liao1fan/schedule-task-mcp.git
cd schedule-task-mcp
npm install
npm run build
Additional setup and usage notes
Register the MCP server with your client to enable task management. You can run the server via a local checkout or reference the built package when you have the compiled entry point.
{
"mcpServers": {
"schedule-task-mcp": {
"command": "npx",
"args": ["-y", "schedule-task-mcp"]
}
}
}
If you are developing from a local checkout, point the client to the compiled entry point after building.
{
"mcpServers": {
"schedule-task-mcp": {
"command": "node",
"args": ["/absolute/path/to/schedule-task-mcp/dist/index.js"]
}
}
}
Core concepts and task management
Key operations you can perform through MCP include creating, listing, inspecting, updating, deleting, pausing, resuming, and executing tasks. You can also clear a task’s run history or query the current scheduler time. The server stores tasks in SQLite at a default location and migrates any legacy data automatically.
Examples of trigger styles you can use: interval, cron, and date (one-time) triggers. You can also use delay-based shortcuts like “in 30 minutes.” For one-time dates, you can specify an explicit timestamp or a relative delay.
MCP Sampling and environment configuration
If you provide agent prompts, the scheduler can invoke MCP Sampling to execute natural-language instructions through your MCP client. You can set environment variables to customize behavior for each client, such as time zone, database path, and sampling timeouts.
Environment variables you may configure include timezone, database path, and sampling timeout. These can be set per MCP client to tailor the scheduler’s behavior to your environment.
Storage and persistence
Tasks are persisted in a SQLite database located at a default path under your home directory. Any legacy data files are migrated automatically on first run to ensure a smooth transition.
Trigger reference
Interval: define a fixed interval in seconds, minutes, hours, or days. Example: every 30 minutes.
Cron: use a five-field cron expression to schedule recurring runs, such as at 09:00 every day or at 09:00 on Mondays.
Date / Delay: for one-off tasks, provide an explicit timestamp or a relative delay (e.g., delay_minutes). If the timestamp is in the past, the server adjusts it automatically.
MCP Sampling workflow overview
When a task with an agent_prompt runs, the server can initiate a sampling flow where your MCP client receives the instruction and executes the task, then records the result in the task history.
Tips for building your own client
To enable sampling, implement a sampling_callback in your MCP client. You can use the official MCP API or an agent framework to handle the workflow and tool execution.
Roadmap highlights
Future enhancements include task dependencies, extended execution history search, web dashboard, retry policies, and webhooks for completion notifications.
Available tools
create_task
Create a new schedule with a name, trigger_type, trigger_config, and optional agent_prompt to enable MCP Sampling.
list_tasks
Display every task with status and next run.
get_task
Inspect a single task by its ID.
update_task
Modify an existing task with any field supported by create_task.
delete_task
Remove a task permanently.
pause_task
Pause a task to stop executions without deleting it.
resume_task
Resume a paused task.
execute_task
Run a task immediately as a manual trigger.
clear_task_history
Wipe the run history for a task while keeping it scheduled.
get_current_time
Return the current time in the configured timezone.