Task Orchestrator
T

Task Orchestrator

A task orchestration and management server based on the MCP protocol, which can break down goals into manageable tasks and track progress, and supports task hierarchical structure and dependency management.
2.5 points
6.1K

What is the Model Context Protocol (MCP) Server?

The Model Context Protocol (MCP) server is a tool for task orchestration and management. It helps users break down goals into manageable tasks and track the completion status of these tasks. Through this server, you can create goals, add tasks, mark task status, and delete tasks.

How to use the Model Context Protocol (MCP) Server?

You can interact with the MCP server by calling the provided APIs. For example, you can create new goals, add tasks and their subtasks, mark tasks as completed, or delete tasks. All operations are performed through a simple command - line interface.

Applicable Scenarios

The MCP server is suitable for various scenarios that require task decomposition and progress tracking, such as software development projects, team collaboration task management, and personal goal planning.

Main Features

Create and Manage Goals
You can create new goals and associate them with specific code repositories. Each goal has a unique ID for subsequent operations.
Task Hierarchical Decomposition
Goals can be decomposed into multiple tasks, and each task can contain subtasks. Task IDs use the dot notation (e.g., '1', '1.1', '1.1.1') for easy management and tracking.
Task Status Tracking
You can mark tasks as completed and view the completion status of tasks. It also supports soft - deleting tasks for later recovery.
Dependency Management
It supports the management of dependencies between tasks to ensure clear logical associations between parent and child tasks.
Persistent Storage
All data is stored in LokiDB to ensure the security and persistence of task and goal information.
Advantages
Provide an intuitive way of task decomposition and management to improve work efficiency
Support complex task dependencies for easy management of complex projects
Easy to integrate into existing development processes to improve the transparency of task execution
Limitations
It may require a certain learning cost for non - technical users
Currently, it does not support a direct graphical interface and mainly relies on command - line operations
Handling subtask dependencies when deleting tasks may increase the complexity of operations

How to Use

Create a Goal
Use the `create_goal` tool to create a new goal, specifying the goal description and the related repository name.
Add Tasks
Use the `add_tasks` tool to add tasks to the goal. If a task is a subtask, specify its parent task ID.
Mark Task Status
Use the `complete_task_status` tool to mark tasks as completed. You can choose whether to recursively complete all subtasks.
Get Task List
Use the `get_tasks` tool to get the list of tasks under the goal. You can choose whether to include subtasks or deleted tasks.
Delete Tasks
Use the `remove_tasks` tool to soft - delete tasks. You can choose whether to delete subtasks at the same time.

Usage Examples

Create Goals and Tasks
The user wants to implement the user authentication function and hopes to break it down into multiple tasks.
Mark Task Status
The user wants to mark a certain task and its subtasks as completed.
Delete Tasks
The user needs to delete a goal that contains subtasks.

Frequently Asked Questions

How to create a new goal?
How to add subtasks?
What are the restrictions when deleting tasks?
How to get the task list?
How to mark a task as completed?

Related Resources

Official Documentation
Complete MCP server documentation, including API references and usage guides.
GitHub Repository
Source code and development information of the MCP server.
Video Tutorial
A video tutorial on using the MCP server, suitable for beginners.

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

A
Airweave
Airweave is an open - source context retrieval layer for AI agents and RAG systems. It connects and synchronizes data from various applications, tools, and databases, and provides relevant, real - time, multi - source contextual information to AI agents through a unified search interface.
Python
7.0K
5 points
V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
5.6K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
5.7K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
5.8K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
5.7K
4 points
P
Paperbanana
Python
7.1K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
7.2K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
7.9K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
25.3K
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
21.9K
4.5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
35.4K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
75.0K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
33.5K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
65.1K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
99.4K
4.7 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
50.8K
4.8 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase