mcpField
T
Task API Server - MCP TypeScript Implementation

Task API Server - MCP TypeScript Implementation

Local
github.com/milkostenProductivity11Updated 86w ago

About Task API Server - MCP TypeScript Implementation

A TypeScript MCP server that connects to an external Task API for AI tooling and web clients. It supports both STDIO and HTTP+SSE, exposing task resources and operations.

Key features

  1. 01Filter tasks by status, category, and priority
  2. 02Create, update, and delete tasks
  3. 03STDIO and HTTP+SSE modes
  4. 04Expose task data structure resources
  5. 05Test client with response validation

Use cases

  1. 01Query and maintain tasks from AI tooling
  2. 02Access task operations through a browser client
  3. 03Find pending tasks by status or category

MCP support

The server exposes task data resources and tools for listing, creating, updating, and deleting tasks to MCP clients. It supports STDIO and HTTP+SSE transports.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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

VariableDescriptionDefault
TASK_MANAGER_API_BASE_URLURL for the external Task APINone (Required)
TASK_MANAGER_API_KEYAPI key for authenticationNone (Required)
TASK_MANAGER_HTTP_PORTPort for the HTTP server3000
PORTAlternative 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

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.