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Task Tracker MCP Server

Name: Task Tracker MCP Server
Author: azamafridi23

by azamafridi23

Overview Schema Source Related Servers Discussions Admin

Python

Remote

📋 Task Tracker MCP Server

Практический сервер Model Context Protocol (MCP), написанный на Python с использованием FastMCP и управляемый с помощью uv. Этот сервер предоставляет AI-ассистентам (таким как Claude Desktop, Cursor, Antigravity и др.) структурированные возможности управления задачами.

🌟 Обзор

Model Context Protocol (MCP) — это открытый стандарт, позволяющий LLM и AI-приложениям безопасно и бесшовно взаимодействовать с внешними инструментами и источниками данных.

Этот проект реализует три основные примитивы MCP:

🛠️ Инструменты: Вызываемые функции, позволяющие модели выполнять действия (add_task, complete_task, delete_task).
📦 Ресурсы: URI только для чтения, позволяющие модели проверять состояние (tasks://all, tasks://pending).
💡 Подсказки: Предопределенные шаблоны подсказок, которые направляют AI на выполнение сложных рабочих процессов (например, анализ задач и расстановка приоритетов).

flowchart LR
    Host["AI Host / Application<br/>(Claude Desktop / Cursor / Antigravity)"] 
    Client["MCP Client<br/>(Protocol Handler)"]
    Server["Task Tracker MCP Server<br/>(FastMCP)"]
    
    Host <--> Client
    Client <--> Server
    
    subgraph ServerCapabilities ["Server Capabilities"]
        Tools["🛠️ Tools<br/>add_task, complete_task, delete_task"]
        Resources["📦 Resources<br/>tasks://all, tasks://pending"]
        Prompts["💡 Prompts<br/>task_summary_prompt"]
    end
    
    Server --- ServerCapabilities

Related MCP server: MCP Task Management Server

🚀 Функции и примитивы MCP

1. Инструменты (Действия)

Инструмент	Аргументы	Описание
`add_task`	`title: str`, `description: str = ""`	Добавляет новую задачу с уникальным ID и временной меткой ISO.
`complete_task`	`task_id: int`	Отмечает статус задачи как `"completed"` и добавляет временную метку завершения.
`delete_task`	`task_id: int`	Удаляет задачу по ID и возвращает удаленный объект.

2. Ресурсы (Данные только для чтения)

URI ресурса	Описание
`tasks://all`	Форматирует и возвращает все задачи с эмодзи (`✅` для выполненных, `⏳` для ожидающих).
`tasks://pending`	Фильтрует и возвращает только активные/ожидающие задачи.

3. Подсказки (Направляемые рабочие процессы)

Подсказка	Описание
`task_summary_prompt`	Направляет AI-ассистента на анализ ожидающих и выполненных задач, выявление просроченных элементов и рекомендацию следующих действий с использованием `tasks://all`.

📦 Начало работы с `uv`

Этот проект создан и управляется с помощью uv — чрезвычайно быстрого менеджера пакетов и проектов Python, написанного на Rust компанией Astral.

1. Установка `uv`

macOS / Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Проверьте установку:

uv --version

2. Клонирование и настройка репозитория

git clone https://github.com/<your-username>/task-tracker-mcp.git
cd task-tracker-mcp

3. Установка зависимостей

uv автоматически создаст виртуальное окружение (.venv) и установит все необходимые зависимости:

uv sync

🧪 Тестирование сервера

Вы можете запустить встроенный асинхронный клиент (test_client.py), который использует каждый инструмент, ресурс и подсказку:

uv run test_client.py

Ожидаемый вывод:

🚀 Starting FastMCP Test Client...
==================================================

1. Listing Available Tools:
   Found 3 tools: ['add_task', 'complete_task', 'delete_task']

2. Calling 'add_task' Tool:
   Task 1 Response: {"id":1,"title":"Learn MCP", ...}
   Task 2 Response: {"id":2,"title":"Master uv", ...}

3. Listing Available Resources:
   Found 2 resources: [AnyUrl('tasks://all'), AnyUrl('tasks://pending')]

4. Reading 'tasks://all' Resource:
   Current Tasks:
   ⏳ [1] Learn MCP
   ⏳ [2] Master uv

5. Completing Task ID 1:
   Completed Result: {"id":1, "status":"completed", ...}

6. Reading 'tasks://pending' Resource:
   Pending Tasks:
   ⏳ [2] Master uv

7. Listing Available Prompts:
   Found 1 prompts: ['task_summary_prompt']

8. Deleting Task ID 2:
   Delete Result: {"success": true, "deleted": {"id": 2, ...}}

==================================================
✨ All MCP Server tests completed successfully!

🔌 Подключение и проверка

1. CLI Inspector и инструменты разработчика FastMCP

FastMCP 3.x предоставляет встроенные CLI-команды для проверки и отладки вашего сервера:

Интерактивный веб-инспектор:
```
uv run fastmcp dev inspector task_server.py
```
Проверка сводки сервера:
```
uv run fastmcp inspect task_server.py
```
Список всех инструментов:
```
uv run fastmcp list task_server.py
```
Запуск автономного сервера:
```
uv run fastmcp run task_server.py
```

2. Интеграция с Claude Desktop

Добавьте конфигурацию сервера в ваш claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "task-tracker": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/task-tracker-mcp",
        "run",
        "task_server.py"
      ]
    }
  }
}

📁 Структура проекта

Task Tracker MCP/
├── pyproject.toml         # Dependency & project metadata (managed by uv)
├── task_server.py         # MCP Server definitions (tools, resources, prompts)
├── test_client.py         # FastMCP async automated test client
├── src/
│   └── task_tracker_mcp/  # Python package entrypoint
│       └── __init__.py
├── .python-version        # Locked Python version
├── .gitignore             # Python & uv exclusions
└── README.md              # Documentation

💡 Шпаргалка по ключевым командам `uv`

Команда	Описание
`uv init`	Инициализация нового проекта Python с `pyproject.toml`
`uv add <pkg>`	Добавление зависимости в `pyproject.toml` и ее установка в `.venv`
`uv remove <pkg>`	Удаление зависимости
`uv run <script.py>`	Запуск любого Python-скрипта в изолированной среде проекта
`uv sync`	Синхронизация установленных пакетов с `uv.lock`
`uv venv`	Явное создание виртуального окружения

🛠️ Следующие шаги и расширения

Постоянное хранение: Замена списка в памяти на SQLite через aiosqlite или sqlite3.
Приоритет и сроки выполнения: Добавление флагов приоритета задач (low, medium, high) и фильтров по срокам выполнения.
Инструмент поиска: Добавление инструмента search_tasks(query: str) для поиска по заголовкам и описаниям.
Аутентификация: Защита конечных точек с помощью провайдеров аутентификации FastMCP.

📄 Лицензия

Этот проект лицензирован на условиях лицензии MIT — подробности см. в файле LICENSE.

Available Tools

3 tools

add_taskC

Add a new task to the task list.

ParametersJSON Schema

Name	Required	Description	Default
`title`	Yes
`description`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

C2.4/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. 'Add' implies a mutation, but nothing is said about required permissions, duplicate handling, defaults for description, or state side effects — a significant gap for a write tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no wasted words, but it is under-specified rather than appropriately concise for a mutation tool with two undocumented parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described. Still, with no annotations and 0% parameter coverage, the definition leaves an agent without enough behavioral or parameter context to reliably invoke a write operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description never mentions any parameter. It does not clarify that 'title' is required or that 'description' defaults to an empty string, so it adds no parameter meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb ('Add') and resource ('a new task to the task list'), so the agent can tell it apart from delete_task and complete_task by operation. However, it offers no differentiation language or scope detail beyond the obvious create/delete/complete split.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites, and no mention of alternatives such as complete_task for status changes. The agent gets a bare purpose statement and must infer all invocation context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

complete_taskC

Mark a task as completed.

ParametersJSON Schema

Name	Required	Description	Default
`task_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

C2.8/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are absent, so the description carries the full behavioral burden. It conveys that this is a state mutation but omits whether the call is idempotent, what happens if the task is already completed, permission requirements, and whether the change is reversible.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero filler, but so terse that it omits information an agent needs rather than being efficiently dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, one required integer parameter, and an output schema exists so return values need not be described. Still, a mutation with no annotations and no parameter documentation leaves gaps around idempotency and error conditions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the undocumented task_id. It only implies 'a task' without stating the identifier format, valid range, or behavior when the id does not exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'Mark a task as completed.' An agent immediately knows the operation. However, it offers no differentiation from siblings like delete_task or add_task, which are the plausible confusions for a task-status mutation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no mention of alternatives, and no note on the distinction between completing and deleting a task. Usage is only weakly implied by the verb.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

delete_taskC

Delete a task from the list.

ParametersJSON Schema

Name	Required	Description	Default
`task_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

C2.6/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. "Delete" implies a destructive mutation but the description says nothing about irreversibility, required permissions, or what happens to the task afterward — significant gaps for a destructive tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single short sentence with no waste and the action front-loaded, which suits a one-parameter tool. However, the brevity comes at the cost of substance rather than being a model of economical communication.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained. But for a destructive mutation with zero annotations and an undocumented parameter, the description omits the safety and side-effect context an agent needs before invoking it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description adds no meaning for task_id beyond what the name implies. The single required integer parameter is nearly self-evident, but nothing explains its origin or format, so the description fails to compensate for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Delete a task"), which is unambiguous against siblings add_task and complete_task, whose verbs already differ. It stops short of explicitly naming those siblings or the scope of deletion, but an agent can distinguish it readily.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites, and no alternatives named. The agent gets no signal about when deleting is appropriate versus completing or leaving a task alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

3 tool updatesv0.1.0Sep 11, 2026
- First observedadd_task
- First observedcomplete_task
- First observeddelete_task

Deploy Server

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TDQS

B3/5.0

Scored 2026-09-11 09:05 across 3 tools

Disambiguation5/5

Each tool targets a clearly distinct action on a task: add, delete, complete. There is no overlap or ambiguity between them, so an agent can easily select the right tool.

Naming Consistency5/5

All three tools follow the exact same verb_noun snake_case pattern (add_task, delete_task, complete_task). Naming is fully predictable.

Tool Count4/5

Three tools is a reasonable, well-scoped set for a minimal task tracker, and each earns its place. It is slightly thin, since a small surface like this leaves little room for the read/lifecycle operations expected of the domain.

Completeness3/5

The set covers create, delete, and a status update, but there is no way to list or retrieve tasks, which is arguably the most essential operation for a tracker. This is a notable gap that will leave agents unable to inspect the task list.

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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📋 Task Tracker MCP Server

🌟 Обзор

🚀 Функции и примитивы MCP

1. Инструменты (Действия)

2. Ресурсы (Данные только для чтения)

3. Подсказки (Направляемые рабочие процессы)

📦 Начало работы с uv

1. Установка uv

2. Клонирование и настройка репозитория

3. Установка зависимостей

🧪 Тестирование сервера

Ожидаемый вывод:

🔌 Подключение и проверка

1. CLI Inspector и инструменты разработчика FastMCP

2. Интеграция с Claude Desktop

📁 Структура проекта

💡 Шпаргалка по ключевым командам uv

🛠️ Следующие шаги и расширения

📄 Лицензия

Available Tools

Output Schema

Output Schema

Output Schema

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

📦 Начало работы с `uv`

1. Установка `uv`

💡 Шпаргалка по ключевым командам `uv`