task-mcp-server

MCP.Pizza Chef: milkosten

The task-mcp-server is a TypeScript-based MCP server implementing a standardized task management API. It connects to external Task API services and supports both CLI (STDIO) and web (HTTP+SSE) communication modes. It offers comprehensive task operations including listing, creating, updating, and deleting tasks, with strong validation and error handling, enabling seamless integration of task workflows into AI agents and applications.

Use This MCP server To

Manage tasks via CLI for AI agent workflows Provide real-time task updates through HTTP+SSE to web clients Create, update, and delete tasks programmatically Filter and list tasks with customizable criteria Integrate task management into AI-enhanced productivity tools

README

Task API Server - MCP TypeScript Implementation

A Model Context Protocol (MCP) implementation for Task Management API written in TypeScript. This project serves as both a reference implementation and a functional task management server.

Overview

This MCP server connects to an external Task API service and provides a standardized interface for task management. It supports two runtime modes:

  1. STDIO Mode: Standard input/output communication for CLI-based applications and AI agents
  2. HTTP+SSE Mode: Web-accessible server with Server-Sent Events for browser and HTTP-based clients

The server offers a complete set of task management operations, extensive validation, and robust error handling.

Features

  • Task Management Operations:

    • List existing tasks with filtering capabilities
    • Create new tasks with customizable properties
    • Update task details (description, status, category, priority)
    • Delete tasks when completed or no longer needed
  • Dual Interface Modes:

    • STDIO protocol support for command-line and AI agent integration
    • HTTP+SSE protocol with web interface for browser-based access
  • MCP Protocol Implementation:

    • Complete implementation of the Model Context Protocol
    • Resources for task data structures
    • Tools for task operations
    • Error handling and informative messages
  • Quality Assurance:

    • Comprehensive test client for validation
    • Automatic server shutdown after tests complete
    • Detailed validation of API responses

Getting Started

Prerequisites

  • Node.js 16.x or higher
  • npm or pnpm package manager

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/mcp-template-ts.git
    cd mcp-template-ts
    
  2. Install dependencies:

    npm install
    

    or using pnpm:

    pnpm install
    
  3. Create an .env file with your Task API credentials:

    TASK_MANAGER_API_BASE_URL=https://your-task-api-url.com/api
    TASK_MANAGER_API_KEY=your_api_key_here
    TASK_MANAGER_HTTP_PORT=3000
    
  4. Build the project:

    npm run build
    

Running the Server

STDIO Mode (for CLI/AI integration)

npm start

or

node dist/index.js

HTTP Mode (for web access)

npm run start:http

or

node dist/http-server.js

By default, the HTTP server runs on port 3000. You can change this by setting the TASK_MANAGER_HTTP_PORT environment variable.

Testing

Run the comprehensive test suite to verify functionality:

npm test

This will:

  1. Build the project
  2. Start a server instance
  3. Connect a test client to the server
  4. Run through all task operations
  5. Verify correct responses
  6. Automatically shut down the server

Using the MCP Client

STDIO Client

To connect to the STDIO server from your application:

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import * as path from 'path';

// Create transport
const transport = new StdioClientTransport({
  command: 'node',
  args: [path.resolve('path/to/dist/index.js')]
});

// Initialize client
const client = new Client(
  {
    name: "your-client-name",
    version: "1.0.0"
  },
  {
    capabilities: {
      prompts: {},
      resources: {},
      tools: {}
    }
  }
);

// Connect to server
await client.connect(transport);

// Example: List all tasks
const listTasksResult = await client.callTool({
  name: "listTasks",
  arguments: {}
});

// Example: Create a new task
const createTaskResult = await client.callTool({
  name: "createTask",
  arguments: {
    task: "Complete project documentation",
    category: "Documentation",
    priority: "high"
  }
});

// Clean up when done
await client.close();

HTTP Client

To connect to the HTTP server from a browser:

<!DOCTYPE html>
<html>
<head>
  <title>Task Manager</title>
  <script type="module">
    import { Client } from 'https://cdn.jsdelivr.net/npm/@modelcontextprotocol/sdk/dist/esm/client/index.js';
    import { SSEClientTransport } from 'https://cdn.jsdelivr.net/npm/@modelcontextprotocol/sdk/dist/esm/client/sse.js';

    document.addEventListener('DOMContentLoaded', async () => {
      // Create transport
      const transport = new SSEClientTransport('http://localhost:3000/mcp');
      
      // Initialize client
      const client = new Client(
        {
          name: "browser-client",
          version: "1.0.0"
        },
        {
          capabilities: {
            prompts: {},
            resources: {},
            tools: {}
          }
        }
      );

      // Connect to server
      await client.connect(transport);
      
      // Now you can use client.callTool() for tasks
    });
  </script>
</head>
<body>
  <h1>Task Manager</h1>
  <!-- Your interface elements here -->
</body>
</html>

Available Tools

listTasks

Lists all available tasks.

const result = await client.callTool({
  name: "listTasks",
  arguments: {
    // Optional filters
    status: "pending", // Filter by status
    category: "Work",  // Filter by category
    priority: "high"   // Filter by priority
  }
});

createTask

Creates a new task.

const result = await client.callTool({
  name: "createTask",
  arguments: {
    task: "Complete the project report",  // Required: task description
    category: "Work",                     // Optional: task category
    priority: "high"                      // Optional: low, medium, high
  }
});

updateTask

Updates an existing task.

const result = await client.callTool({
  name: "updateTask",
  arguments: {
    taskId: 123,                       // Required: ID of task to update
    task: "Updated task description",  // Optional: new description
    status: "done",                    // Optional: pending, started, done
    category: "Personal",              // Optional: new category
    priority: "medium"                 // Optional: low, medium, high
  }
});

deleteTask

Deletes a task.

const result = await client.callTool({
  name: "deleteTask",
  arguments: {
    taskId: 123  // Required: ID of task to delete
  }
});

Environment Variables

Variable Description Default
TASK_MANAGER_API_BASE_URL URL for the external Task API None (Required)
TASK_MANAGER_API_KEY API key for authentication None (Required)
TASK_MANAGER_HTTP_PORT Port for the HTTP server 3000
PORT Alternative port name (takes precedence) None

Project Structure

mcp-template-ts/
├── dist/               # Compiled JavaScript files
├── src/                # TypeScript source files
│   ├── index.ts        # STDIO server entry point
│   ├── http-server.ts  # HTTP+SSE server entry point
│   ├── test-client.ts  # Test client implementation
├── .env                # Environment variables
├── package.json        # Project dependencies
├── tsconfig.json       # TypeScript configuration
└── README.md           # Project documentation

Development

  1. Start the TypeScript compiler in watch mode:

    npm run watch
    
  2. Run tests to verify changes:

    npm test
    

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • This project uses the @modelcontextprotocol/sdk for MCP protocol implementation
  • Built for integration with AI tooling and web applications

task-mcp-server FAQ

How does task-mcp-server communicate with clients?
It supports STDIO for CLI apps and HTTP+SSE for web clients.
What task operations are supported?
Listing, creating, updating, and deleting tasks with validation.
Can I filter tasks when listing?
Yes, the server supports filtering tasks by various criteria.
Is task-mcp-server suitable for real-time task updates?
Yes, it uses Server-Sent Events (SSE) for live updates.
What programming language is task-mcp-server implemented in?
It is implemented in TypeScript.
Does task-mcp-server handle error validation?
Yes, it includes extensive validation and robust error handling.
Can this server be integrated with AI models like OpenAI, Claude, or Gemini?
Yes, it provides a standardized MCP interface compatible with these LLM providers.
What runtime modes does task-mcp-server support?
STDIO mode for CLI and HTTP+SSE mode for web clients.