Model Context Protocol (MCP) server for scheduling and managing tasks through a standardized API. The server provides task scheduling capabilities supporting both shell commands and AI-powered tasks, all accessible via the MCP protocol.

Features

Schedule shell command or prompt to AI tasks using cron expressions
AI can have access to MCP servers
Manage tasks via MCP protocol
Task execution with command output capture
Task persistence across restarts (SQLite)
Multi-instance safe — multiple instances can share the same database without duplicate execution
Support multiple isolated instances with different --db-path

Installation

npm (recommended)

npx -y mcp-cron

Claude Code

claude mcp add mcp-cron -- npx -y mcp-cron

Cursor / Claude Desktop

{
  "mcpServers": {
    "mcp-cron": {
      "command": "npx",
      "args": ["-y", "mcp-cron", "--transport", "stdio"]
    }
  }
}

Recommended Configuration

A more complete setup with AI provider, model selection, and sleep prevention:

{
  "mcpServers": {
    "mcp-cron": {
      "command": "npx",
      "args": [
        "-y", "mcp-cron",
        "--transport", "stdio",
        "--prevent-sleep",
        "--ai-provider", "anthropic",
        "--ai-model", "claude-sonnet-4-5-20250929"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-api-key"
      }
    }
  }
}

Using LiteLLM

To route AI tasks through a LiteLLM proxy:

{
  "mcpServers": {
    "mcp-cron": {
      "command": "npx",
      "args": [
        "-y", "mcp-cron",
        "--transport", "stdio",
        "--prevent-sleep",
        "--ai-base-url", "https://litellm.yourcompany.com",
        "--ai-model", "claude-sonnet-4-5-20250929"
      ],
      "env": {
        "MCP_CRON_AI_API_KEY": "sk-your-litellm-key"
      }
    }
  }
}

The --ai-model value should match a model name in your LiteLLM proxy config. LiteLLM exposes an OpenAI-compatible API, so --ai-provider can be omitted (defaults to openai). When a custom base URL is set, mcp-cron automatically uses the Chat Completions API instead of the Responses API. The Responses API is only used for direct OpenAI (api.openai.com) and Azure OpenAI (*.openai.azure.com) endpoints.

See Command Line Arguments and Environment Variables for all available options.

Building from Source

Prerequisites

Go 1.24.0 or higher

# Clone the repository
git clone https://github.com/jolks/mcp-cron.git
cd mcp-cron

# Build the application as mcp-cron binary
go build -o mcp-cron cmd/mcp-cron/main.go

Usage

The server supports two transport modes:

HTTP (Streamable HTTP): Default HTTP-based transport for browser and network clients
stdio: Standard input/output transport for direct piping and inter-process communication

Client	Config File Location
Cursor	`~/.cursor/mcp.json`
Claude Desktop (Mac)	`~/Library/Application Support/Claude/claude_desktop_config.json`
Claude Desktop (Windows)	`%APPDATA%\Claude\claude_desktop_config.json`

HTTP (Streamable HTTP)

# Start the server with Streamable HTTP transport (default mode)
# Default to localhost:8080
./mcp-cron

# Start with custom address and port
./mcp-cron --address 127.0.0.1 --port 9090

Config file example

{
  "mcpServers": {
    "mcp-cron": {
      "url": "http://localhost:8080"
    }
  }
}

stdio

The stdio transport is particularly useful for:

Direct piping to/from other processes
Integration with CLI tools
Testing in environments without HTTP
Docker container integration

Upon starting Cursor IDE and Claude Desktop, it will automatically start the server

Config file example

{
  "mcpServers": {
    "mcp-cron": {
      "command": "<path to where mcp-cron binary is located>/mcp-cron",
      "args": ["--transport", "stdio"]
    }
  }
}

Command Line Arguments

The following command line arguments are supported:

Argument	Description	Default
`--address`	The address to bind the server to	`localhost`
`--port`	The port to bind the server to	`8080`
`--transport`	Transport mode: `http` or `stdio`	`http`
`--log-level`	Logging level: `debug`, `info`, `warn`, `error`, `fatal`	`info`
`--log-file`	Log file path	stdout
`--version`	Show version information and exit	`false`
`--ai-provider`	AI provider: `openai` or `anthropic`	`openai`
`--ai-base-url`	Custom base URL for OpenAI-compatible endpoints (e.g. Ollama, vLLM, Groq, LiteLLM)	Not set
`--ai-model`	AI model to use for AI tasks	`gpt-4o`
`--ai-max-iterations`	Maximum iterations for tool-enabled AI tasks	`20`
`--mcp-config-path`	Path to MCP configuration file	`~/.cursor/mcp.json`
`--db-path`	Path to SQLite database for result history	`~/.mcp-cron/results.db`
`--prevent-sleep`	Prevent system from sleeping while mcp-cron is running (macOS and Windows)	`false`
`--poll-interval`	How often to check for due tasks	`1s`

Environment Variables

The following environment variables are supported:

Environment Variable	Description	Default
`MCP_CRON_SERVER_ADDRESS`	The address to bind the server to	`localhost`
`MCP_CRON_SERVER_PORT`	The port to bind the server to	`8080`
`MCP_CRON_SERVER_TRANSPORT`	Transport mode: `http` or `stdio`	`http`
`MCP_CRON_SERVER_NAME`	Deprecated — ignored; the server name is fixed to ensure self-reference detection works correctly	-
`MCP_CRON_SERVER_VERSION`	Deprecated — ignored; version is set at build time via ldflags	-
`MCP_CRON_SCHEDULER_DEFAULT_TIMEOUT`	Default timeout for task execution	`10m`
`MCP_CRON_LOGGING_LEVEL`	Logging level: `debug`, `info`, `warn`, `error`, `fatal`	`info`
`MCP_CRON_LOGGING_FILE`	Log file path	stdout
`MCP_CRON_AI_PROVIDER`	AI provider: `openai` or `anthropic`	`openai`
`MCP_CRON_AI_BASE_URL`	Custom base URL for OpenAI-compatible endpoints (e.g. Ollama, vLLM, Groq, LiteLLM)	Not set
`MCP_CRON_AI_API_KEY`	Generic fallback API key (used when provider-specific key is not set)	Not set
`OPENAI_API_KEY`	OpenAI API key for AI tasks	Not set
`ANTHROPIC_API_KEY`	Anthropic API key for AI tasks	Not set
`MCP_CRON_ENABLE_OPENAI_TESTS`	Enable OpenAI integration tests	`false`
`MCP_CRON_AI_MODEL`	LLM model to use for AI tasks	`gpt-4o`
`MCP_CRON_AI_MAX_TOOL_ITERATIONS`	Maximum iterations for tool-enabled tasks	`20`
`MCP_CRON_MCP_CONFIG_FILE_PATH`	Path to MCP configuration file	`~/.cursor/mcp.json`
`MCP_CRON_STORE_DB_PATH`	Path to SQLite database for result history	`~/.mcp-cron/results.db`
`MCP_CRON_PREVENT_SLEEP`	Prevent system from sleeping while mcp-cron is running (macOS and Windows)	`false`
`MCP_CRON_POLL_INTERVAL`	How often to check for due tasks (Go duration format)	`1s`

Sleep Prevention

On laptops, the system may go to sleep and prevent scheduled tasks from running on time. Use the --prevent-sleep flag to keep the system awake while mcp-cron is running:

mcp-cron --prevent-sleep --transport stdio

Or via environment variable:

MCP_CRON_PREVENT_SLEEP=true mcp-cron --transport stdio

Platform	Mechanism	Notes
macOS	`caffeinate`	Prevents idle sleep; automatically cleans up on exit
Windows	`SetThreadExecutionState`	Prevents idle sleep; automatically cleans up on exit
Linux	Not supported	Linux servers typically do not auto-sleep

Note: This prevents idle sleep only. It does not prevent sleep from closing the laptop lid or pressing the power button.

Logging

When running with the default HTTP transport, logs are output to the console.

When running with stdio transport, logs are redirected to a mcp-cron.log log file to prevent interference with the JSON-RPC protocol:

Log file location: Same location as mcp-cron binary.
Task outputs, execution details, and server diagnostics are written to this file.
The stdout/stderr streams are kept clean for protocol messages only.

Available MCP Tools

The server exposes several tools through the MCP protocol:

list_tasks - Lists all tasks (scheduled and on-demand)
get_task - Gets a specific task by ID
add_task - Adds a new shell command task (provide schedule for recurring, or omit for on-demand)
add_ai_task - Adds a new AI (LLM) task with a prompt (provide schedule for recurring, or omit for on-demand)
add_http_task - Adds a new HTTP (webhook) task that issues an HTTP request to a url (provide schedule for recurring, or omit for on-demand)
update_task - Updates an existing task
remove_task - Removes a task by ID
run_task - Executes a task by ID, waits for completion, and returns the result (for on-demand tasks or ad-hoc runs of scheduled tasks)
enable_task - Enables a task so it runs on its schedule or can be triggered via run_task
disable_task - Disables a task so it stops running and cannot be triggered
get_task_result - Gets execution results for a task (latest by default, or recent history with limit)
query_task_result - Runs a read-only SQL query against the database (SELECT only, capped at 1000 rows)

Task Format

Tasks have the following structure:

{
  "id": "task_a3f7b2c9e1d04f68",
  "name": "Example Task",
  "schedule": "0 */5 * * * *",
  "command": "echo 'Task executed!'",
  "prompt": "Analyze yesterday's sales data and provide a summary",
  "type": "shell_command",
  "description": "An example task that runs every 5 minutes",
  "enabled": true,
  "lastRun": "2025-01-01T12:00:00Z",
  "nextRun": "2025-01-01T12:05:00Z",
  "status": "completed",
  "createdAt": "2025-01-01T00:00:00Z",
  "updatedAt": "2025-01-01T12:00:00Z"
}

The type field can be shell_command (default), AI, or http. The fields that apply depend on the type:

shell_command — command: the shell command to execute.
AI — prompt: what the AI should do.
http — url (required), method (defaults to POST), headers (JSON object of string→string), and body (request body string). Created via add_http_task.

For HTTP tasks, the result row reuses the existing columns:

Result field	Meaning for HTTP tasks
`exit_code`	HTTP status code (0 if no response was received)
`output`	Response body preview (capped at 8 KiB, suffixed `... (truncated)`)
`error`	Transport error, build-request error, or `non-2xx status: N <reason>`
`duration`	Round-trip latency
`url`	The request URL

This keeps query_task_result queries uniform — e.g. SELECT COUNT(*) FROM results WHERE task_id='x' AND exit_code >= 200 AND exit_code < 300 counts successful HTTP calls.

Scheduled vs on-demand tasks:

Scheduled: Provide a schedule (cron expression) — the task runs automatically on that schedule.
On-demand: Omit schedule — the task sits idle until triggered via run_task.

run_task also works on scheduled tasks for ad-hoc execution outside their normal schedule. After execution, scheduled tasks resume their normal schedule; on-demand tasks return to idle.

Task Status

The tasks can have the following status values:

pending - Task has not been run yet
running - Task is currently running
completed - Task has successfully completed
failed - Task has failed during execution
disabled - Task is disabled and won't run on schedule

Cron Expression Format

Cron expressions are required for scheduled tasks and omitted for on-demand tasks. The scheduler uses the github.com/robfig/cron/v3 library for parsing. The format includes seconds:

┌───────────── second (0 - 59) (Optional)
│ ┌───────────── minute (0 - 59)
│ │ ┌───────────── hour (0 - 23)
│ │ │ ┌───────────── day of the month (1 - 31)
│ │ │ │ ┌───────────── month (1 - 12)
│ │ │ │ │ ┌───────────── day of the week (0 - 6) (Sunday to Saturday)
│ │ │ │ │ │
│ │ │ │ │ │
* * * * * *

Examples:

0 */5 * * * * - Every 5 minutes (at 0 seconds)
0 0 * * * * - Every hour
0 0 0 * * * - Every day at midnight
0 0 12 * * MON-FRI - Every weekday at noon

Development

Building

go build -o mcp-cron cmd/mcp-cron/main.go

Testing

See docs/testing.md for the full testing guide, including integration tests and AI task tests.

Acknowledgments

modelcontextprotocol/go-sdk - Official Go SDK for the Model Context Protocol
robfig/cron - Cron expression parsing for Go

MCP Cron