MCP Todo Server (TypeScript)
MCP Todo Server (TypeScript)
MCP 基础服务器,用于管理存储在本地 JSON 文件中的待办事项列表。为 UNA 编程 IV 课程的课外作业 1 (MCP) 而制作。
暴露的能力
类型 | 名称 | 描述 |
Resource |
| 返回 JSON 格式的完整任务列表 |
Tool |
| 添加新任务 |
Tool |
| 将任务标记为已完成 |
Prompt |
| 生成任务状态摘要 |
Related MCP server: Todo MCP Server
安装
克隆此仓库并进入文件夹:
git clone <url-del-repo> cd mcp-todo-server-ts安装依赖:
npm install编译 TypeScript 项目:
npm run build
运行
使用官方 MCP Inspector(Web 界面,无需 Claude Desktop 即可调用 resource、tools 和 prompt)测试服务器:
npm run inspector直接运行:
npm start连接 Claude Desktop
请参阅本作业练习 3 中 claude_desktop_config.json 配置部分的说明。要注册的命令指向编译后的文件,例如:
{
"mcpServers": {
"todo-server": {
"command": "node",
"args": ["C:\\ruta\\completa\\a\\mcp-todo-server-ts\\build\\server.js"]
}
}
}项目结构
mcp-todo-server-ts/
├── src/
│ └── server.ts # Servidor MCP principal (código fuente)
├── build/ # Generado por "npm run build" (no se sube a git)
├── tasks.json # Almacenamiento de tareas
├── package.json # Dependencias y scripts
├── tsconfig.json # Configuración de TypeScript
└── README.md # Este archivo已完成的测试
(请用 npm run inspector 的截图补充,至少展示 3 次交互:例如,添加两个任务并完成一个,以及查询 resource 和 daily_summary 提示。)
Available Tools
2 toolsadd_taskB
Agrega una nueva tarea con nombre, descripcion y prioridad
| Name | Required | Description | Default |
|---|---|---|---|
| nombre | Yes | Nombre corto de la tarea | |
| prioridad | Yes | Prioridad de la tarea | |
| descripcion | Yes | Detalle de la tarea |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the action and fields, omitting behavioral details such as return value, idempotency, duplicate handling, or any side effects. This is insufficient for a creation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded Spanish sentence with no superfluous words. It efficiently conveys the core action and inputs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description lacks key contextual details such as what is returned after creation, constraints on the task (e.g., uniqueness), or how it relates to the sibling 'complete_task'. It is minimally complete but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description merely lists the parameters ('nombre, descripcion y prioridad') without adding new meaning or usage context beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'agrega' (adds) and the resource 'nueva tarea' (new task), mentioning the three fields. It is specific and avoids tautology. It could be a 5 if it distinguished from the sibling 'complete_task', but it does not.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for creating tasks, but provides no explicit when-to-use or alternatives to the sibling tool 'complete_task'. The context is clear from the name, but no exclusions or guidance is given, so a middle score is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
complete_taskC
Marca una tarea como completada dado su id
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes | Id numerico de la tarea a completar |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a state change (mark as completed) but does not disclose any behavioral traits such as reversibility, side effects, or required permissions. Without annotations, more transparency is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. It is efficient but could benefit from slight expansion to improve completeness without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description adequately covers the core action. However, it lacks context about side effects, usage boundaries, and alternatives, which limits completeness for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has one parameter (task_id) which is already described in the input schema. The tool description adds no additional meaning beyond that. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (marca/completa) and resource (tarea/task) along with the input (id). It distinguishes the action from the sibling tool 'add_task' by focusing on completion rather than creation, but does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks any context about prerequisites, when not to use it, or reference to the sibling tool 'add_task'.
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.
2 tool updates
v1.0.0- First observed
add_task - First observed
complete_task
TDQS
Scored across 2 tools
Only two tools exist, 'add_task' and 'complete_task', each with a clearly distinct purpose: creating a task vs marking it complete. No overlap or ambiguity.
Both tools follow a consistent verb_noun pattern in snake_case (add_task, complete_task), making the naming predictable and easy to understand.
With only two tools, the server is too minimal for a typical todo server. Essential operations like listing, getting, updating, and deleting tasks are missing, making it feel incomplete for its intended scope.
The tool surface is severely incomplete for a todo server. There is no way to view tasks, update task details, delete tasks, or query specific tasks. The agent can only add and complete, which is insufficient.
Maintenance
Related MCP Connectors
Create, list, and complete todo items through MCP.
Nifty's MCP server — exposes tasks, projects, messages, and files as tools for AI agents.
- mcpOAuthnet.todoist
Official Todoist MCP server for AI assistants to manage tasks, projects, and workflows.
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