Task Manager MCP Server

by MustakAhmedcse

239 downloads

Not rated

GitHub

Productivity

Description

# Task Manager MCP Server ## Overview This project is a **Task Manager MCP Server** designed to manage tasks efficiently using tools connected to a database. It provides APIs for adding, viewing, completing, and deleting tasks, and integrates with LangChain for AI-driven task…

About

Details

Author: MustakAhmedcse
Downloads: 239
Categories: Productivity

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Task Manager MCP Server

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

From the repository

Clone the repository, install dependencies with pip install -r requirements.txt, then start the MCP server by running python server.py. To use the graphical interface, run streamlit run streamlit.py. Debugging configurations are available in .vscode/launch.json.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "task manager mcp server": {
            "to-do-app-mcp-server": {
                "command": "python",
                "args": [
                    "server.py"
                ]
            }
        }
    }
}

McpServers

{
    "to-do-app-mcp-server": {
        "command": "python",
        "args": [
            "server.py"
        ]
    }
}

Task Manager MCP Server

Overview

This project is a Task Manager MCP Server designed to manage tasks efficiently using tools connected to a database. It provides APIs for adding, viewing, completing, and deleting tasks, and integrates with LangChain for AI-driven task management.

Features

- Task Management: Add, list, complete, and remove tasks.
- Streamlit Integration: A user-friendly interface for interacting with the task manager.
- AI Assistance: Uses LangChain to provide intelligent responses and manage tasks.
- Tool Integration: Connects to external tools for enhanced functionality.

Project Structure

├── agent.py          # Handles AI interactions and tool calls.
├── client.py         # Connects to the server using SSE.
├── config.py         # Configuration settings for models and server.
├── logger.py         # Logging utility for debugging.
├── models.py         # Creates and configures language models.
├── server.py         # Implements the MCP server and task management tools.
├── streamlit.py      # Streamlit-based UI for task management.
├── task.py           # Defines the Task model using Pydantic.
├── task_manager.py   # Manages the task list and operations.
├── tools.py          # Handles tool loading and execution.
├── requirements.txt  # Lists project dependencies.
├── .gitignore        # Specifies files to ignore in version control.
├── .vscode/          # VS Code configuration for debugging.
└── README.md         # Project documentation.

Installation

1. Clone the repository:

   git clone <repository-url>

   cd <repository-folder>

2. Install dependencies:

   pip install -r requirements.txt

Usage

Running the Server

Start the MCP server:

python server.py

Running the Streamlit UI

Launch the Streamlit interface:

streamlit run streamlit.py

Debugging

Use the VS Code debugger configurations in .vscode/launch.json.

Key Components

Server

The server (server.py) provides tools for task management:

- list_tasks: Lists all tasks.
- add_task: Adds a new task.
- remove_task: Removes a task by ID.
- mark_complete: Marks a task as complete.

Streamlit UI

The Streamlit interface (streamlit.py) allows users to interact with the task manager visually.

AI Agent

The AI agent (agent.py) uses LangChain to process user queries and interact with tools.

Dependencies

See requirements.txt for a complete list of dependencies.

No reviews yet — be the first

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.

Description

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Task Manager MCP Server

Overview

Features

Project Structure

Installation

Usage

Running the Server

Running the Streamlit UI

Debugging

Key Components

Server

Streamlit UI

AI Agent

Dependencies

Install

More like this

Time

Github SSE

Npx Y convex@latest mcp start

Inbox Zero

Lamda

Windows-MCP