mcp-task-orchestrator

🥈Silver

MCP Task Orchestrator is a server that enables AI assistants to manage and coordinate tasks. It benefits operations teams by automating workflows and integrating with AI agents. The tool connects to Python-based systems and supports Claude AI agents.

24120Updated Today

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/EchoingVesper/mcp-task-orchestrator.git

Works with:

Claude

Overview

About This Skill

The mcp-task-orchestrator is a Model Context Protocol server designed to provide robust task orchestration capabilities for AI assistants. By leveraging this Claude Code skill, users can efficiently manage and coordinate tasks within AI workflows, enabling seamless interaction and operation of AI agents. This skill is particularly beneficial for developers and product managers looking to enhance their AI automation processes and improve overall workflow efficiency. One of the key benefits of the mcp-task-orchestrator is its ability to streamline complex task management, allowing teams to focus on higher-level strategic initiatives rather than getting bogged down in manual task coordination. While specific time savings are not quantified, the skill's intermediate implementation time of just 30 minutes suggests that users can quickly integrate it into their existing systems, leading to immediate productivity gains. This skill is ideal for developers and AI practitioners who are involved in building and managing AI agents. It fits well within AI-first workflows, where automation and orchestration are crucial for maximizing the potential of AI technologies. Practical use cases include automating data processing tasks, coordinating responses from multiple AI agents, and enhancing user interactions through more organized task management. With an intermediate complexity level, the mcp-task-orchestrator requires some familiarity with AI automation concepts but is accessible enough for those with a basic understanding of AI workflows. By incorporating this skill into your AI toolkit, you can unlock new efficiencies and elevate the capabilities of your AI assistants, making it a valuable addition to any automation strategy.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/EchoingVesper/mcp-task-orchestrator

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I need to set up a task orchestration workflow for [COMPANY] in the [INDUSTRY] sector. The workflow should involve [NUMBER] tasks, including data processing, analysis, and reporting. The tasks should be coordinated and managed by an AI assistant using the MCP Task Orchestrator. Provide a step-by-step guide to implement this workflow, including the necessary Python code snippets and integration points with Claude AI agents.

Example Output

## Task Orchestration Workflow for [COMPANY] in the [INDUSTRY] Sector

### Workflow Overview
The workflow involves [NUMBER] tasks:
- Data Collection
- Data Processing
- Data Analysis
- Reporting

### Step-by-Step Implementation
1. **Set Up the MCP Task Orchestrator Server**
   - Install the MCP Task Orchestrator server on your preferred platform.
   - Configure the server to support Claude AI agents.

2. **Define the Tasks**
   ```python
   tasks = [
       {"name": "Data Collection", "description": "Collect data from various sources"},
       {"name": "Data Processing", "description": "Process the collected data"},
       {"name": "Data Analysis", "description": "Analyze the processed data"},
       {"name": "Reporting", "description": "Generate reports based on the analysis"}
   ]
   ```

3. **Integrate with Claude AI Agents**
   - Use the MCP Task Orchestrator API to integrate with Claude AI agents.
   - Ensure the agents are properly authenticated and authorized.

4. **Monitor and Manage the Workflow**
   - Use the MCP Task Orchestrator dashboard to monitor the progress of each task.
   - Handle any errors or issues that arise during the execution of the tasks.

### Expected Outcomes
- Automated and coordinated task execution.
- Improved efficiency and accuracy in data processing and analysis.
- Enhanced reporting capabilities with real-time data insights.