Task Tracker MCP Server

Overview

This project is a Model Context Protocol (MCP) server that acts as a bridge to a task-tracking application backend. It handles authentication against the backend and exposes a set of tools and resources that an MCP client (like a large language model or an AI assistant) can use to interact with the task management system.

The server is built using Python and the fastmcp library. On startup, it authenticates with the backend using credentials provided via a .env file and maintains an authenticated session for all subsequent API calls.

Available Tools

The following tools, resources, and prompts are exposed by this MCP server:

Tools

• get_tasks(project_id: Optional[int], assigned_user_id: Optional[int]) -> Dict
  • Retrieves tasks from the backend.
  • Can be filtered by project_id.
  • If assigned_user_id is not provided, it defaults to fetching tasks assigned to the currently authenticated agent.

Installation and Setup

1. Clone the repository:

   git clone <repository-url>
   cd task-tracker-mcp-server-python-fastmcp

2. Create and activate a virtual environment using uv:

   uv venv
   source .venv/bin/activate

3. Install dependencies using uv: The project's dependencies are defined in pyproject.toml and locked in uv.lock. Use uv sync to install them.

   uv sync

4. Create a .env file: This server loads configuration from a .env file in the project root. Create this file and add the necessary credentials:

   BACKEND_URL="http://your-backend-api-url.com"
   TASKAPP_USER="your-username"
   TASKAPP_PASSWORD="your-password"
   

Testing with MCP Inspector

Once the server is configured, you can test it locally.

1. Run the server:

   uv run mcp run main.py

   On startup, the server will attempt to log in to the backend. You should see log messages indicating success or failure.

2. Use the MCP Inspector: In a separate terminal (with the virtual environment activated), use the mcp CLI to inspect the running server and test its tools.

   uv run mcp dev main.py

   This will open an interactive inspector where you can see available tools and call them. For example, to call the get_tasks tool:

   call get_tasks --params '{"project_id": 1}'
   

Configuration in Zed

To use this MCP server with the Zed editor, you need to configure it in your settings.json file.

1. Open Zed and go to File > Settings (or Cmd + ,).
2. Click "Open JSON" to edit the settings.json file.
3. Add the following configuration to the context_servers list.

{
"context_servers": {
  "taskapp-mcp-server": {
    "source": "custom",
    "command": "uv",
    "args": [
      "run",
      "--with",
      "mcp,httpx",
      "mcp",
      "run",
      "main.py"
    ],
    "env": {
      "BACKEND_URL": "your_url_to_the_backend",
      "TASKAPP_USER": "your_username",
      "TASKAPP_PASSWORD": "your_password"
    }
  },

After saving the settings, Zed will be able to communicate with your MCP server.