Task Manager MCP Server

@MustakAhmedcse

Repository

Basic information

About Task Manager MCP Server

No overview available yet

#task-manager #mcp-server #ai-assistant

Task Manager MCP Server config

Add this server to your MCP-compatible client using the configuration below.

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

Task Manager MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Task Manager MCP Server?

Task Manager MCP Server is a task management tool that integrates with a database and uses LangChain for AI‑driven assistance. It provides APIs for adding, viewing, completing, and deleting tasks, and includes a Streamlit‑based user interface. This server is designed for developers and users who want to manage tasks programmatically or through a visual interface with AI support.

How to use Task Manager MCP Server?

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.

Key features of Task Manager MCP Server

Add, list, complete, and remove tasks.
Streamlit‑based user interface for visual interaction.
LangChain integration for intelligent task management.
Tool‑based architecture connecting to external tools.
Structured project with separate modules for server, agent, and UI.

Use cases of Task Manager MCP Server

Rapidly build a task management application with a backend server.
Manage tasks through an AI agent that processes natural language queries.
Debug and test task operations using a Streamlit frontend.
Integrate task management into larger LangChain‑powered workflows.

Frequently asked questions

What does the server do?

The server manages tasks 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.

How do I run the server and the UI?

Start the MCP server by running `python server.py`. For the graphical interface, run `streamlit run streamlit.py`.

What are the dependencies?

All dependencies are listed in `requirements.txt`. Install them with `pip install -r requirements.txt`.

What tools are available on the server?

The server provides four tools: `list_tasks` (list all tasks), `add_task` (add a new task), `remove_task` (remove a task by ID), and `mark_complete` (mark a task as complete).

How does the AI agent work?

The AI agent in `agent.py` uses LangChain to process user queries and interact with the task management tools, enabling intelligent responses and task operations.

Comments

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